├── src └── pssmpro │ ├── __init__.py │ ├── data │ ├── __init__.py │ ├── pssm_files │ │ ├── __init__.py │ │ ├── example_2.pssm │ │ └── example_1.pssm │ └── example.fasta │ └── features.py ├── MANIFEST.in ├── pyproject.toml ├── .gitignore ├── setup.cfg ├── LICENSE └── README.md /src/pssmpro/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/pssmpro/data/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /src/pssmpro/data/pssm_files/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- 1 | include src/pssmpro/data/example.fasta 2 | include src/pssmpro/data/pssm_files/* -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [build-system] 2 | requires = [ 3 | "setuptools>=42", 4 | "wheel", 5 | ] 6 | build-backend = "setuptools.build_meta" -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | **/.idea 2 | **/__pycache__ 3 | .DS_Store 4 | **/tmp 5 | README.ipynb 6 | build 7 | dist 8 | src/pssmpro.egg-info 9 | **/.ipynb_checkpoints 10 | .git/ -------------------------------------------------------------------------------- /src/pssmpro/data/example.fasta: -------------------------------------------------------------------------------- 1 | >gi|52628659|gb|AAU27400.1| hypothetical protein lpg1317 [Legionella pneumophila subsp. pneumophila str. Philadelphia 1]|1 2 | MKQKIDYIARYFKLMSPIINREEINNIVKAQDELEITGAPEHGSHKLSIVKELETGFEYVQKQTKNQTETEKEFMMASFLNKVNPNHPKCKLVETNNGSVSILSRKQENTQDVEQFVRAGRTNELLEKKVIGLEDTLIADNILGKQSDTKLANMLVKDEGDTLVFSNIDHERANLPTFSLFNSGQRRYPTSAHELVSGIADLYEPSDDNRSGLAGDKRAKEFGEVATKVIKQEKIKSAYEKVANADIDSVYKKCSSLSQNSTFFGGKNNCNAYRQYFKEIQKEAADTVSKFDLKK 3 | >gi|33594166|ref|NP_881810.1| ribulose-phosphate 3-epimerase [Bordetella pertussis Tohama I]|-1 4 | MHIMPPEIANTMSTQPASTRIAPSILSADFARLGEEVRNVVAAGADWIHFDVMDNHYVPNLTIGPMVCAAIRPHVQVPIDVHLMVEPVDEIVPQFAKAGANVITFHPEASRHVDRTLALIRDHGCKAGLVFNPATPLHYMDYVMDKLDVVLLMSVNPGFGGQAFIPATLAKLRDARARIDRWRAAGGQPILLEVDGGVKVDNIAEIRAAGADTFVAGSAIFGKPDYAQVIGQLRAEIARGETIAV 5 | -------------------------------------------------------------------------------- /setup.cfg: -------------------------------------------------------------------------------- 1 | [metadata] 2 | name = pssmpro 3 | version = 0.0.2 4 | author = Deepro Banerjee 5 | author_email = deepro.2.4@gmail.com 6 | description = A python tool for numerically encoding protein sequences based on position specific scoring matrices 7 | long_description = file: README.md 8 | long_description_content_type = text/markdown 9 | url = https://github.com/deeprob/pssmpro.git 10 | classifiers = 11 | Programming Language :: Python :: 3 12 | License :: OSI Approved :: MIT License 13 | Operating System :: OS Independent 14 | 15 | [options] 16 | package_dir = 17 | = src 18 | packages = find: 19 | include_package_data = True 20 | python_requires = >=3.0 21 | install_requires = 22 | numpy 23 | 24 | [options.packages.find] 25 | where = src 26 | 27 | [options.package_data] 28 | * = 29 | pssmpro/data/example.fasta 30 | pssmpro/data/pssm_files/* -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 Deepro Banerjee 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | [![DOI](https://zenodo.org/badge/371429755.svg)](https://zenodo.org/badge/latestdoi/371429755) 4 | 5 | # Tutorial 6 | 7 | ## Generating PSSM profiles 8 | 9 | To generate PSSM profiles for protein sequences, the helper function *create_pssm_profile* can be used. However, before using the function, the steps mentioned below must be followed. 10 | 11 | - Download a blast database: For eg. uniref50 database can be downloaded using this link 12 | 13 | http://ftp.ebi.ac.uk/pub/databases/uniprot/uniref/uniref50/ 14 | 15 | 16 | - Download blast executables using this link preferably version 2.9.0. The psiblast program used to create the PSSM profiles will be downloaded as well along with makeblastdb program to be used in the next step 17 | 18 | https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/ 19 | 20 | 21 | - Make a local blast database using uniref50 fasta file and the blast executable (makeblastdb). The following command can be used for that purpose. 22 | 23 | \$makeblastdb -in uniref50.fasta -dbtype prot -out uniref50 24 | 25 | For further information, refer here: 26 | 27 | https://quickgrid.blogspot.com/2018/10/Python-Sub-Process-Local-Psi-Blast-PSSM-Generation-from-FASTA-in-Directory-using-Uniref50-Database-in-Pycharm.html 28 | 29 | 30 | Once the above steps have been followed and there is an indexed blast database on your local machine, the *create_pssm_profile* function can be used. It requires the following arguments: 31 | 32 | 1. A comma separated protein sequence file where each line contains the name of the protein followed by its sequence separated by a comma. 33 | 34 | 2. The output directory where the user would like to store the pssm profiles. 35 | 36 | 3. The path of the psiblast program executable downloaded in step 2 described above. 37 | 38 | 4. The path of the indexed blast database directory created in step 3 described above. 39 | 40 | 41 | 42 | ```python 43 | # Usage example 44 | 45 | from pssmpro.features import create_pssm_profile 46 | 47 | # The comma separated protein sequence file 48 | protein_sequence_file = "./pssmpro_test_data/test_seq.csv" 49 | # Output directory where the pssm profiles will be stored 50 | output_dir = "./pssmpro_test_data/pssm_profiles/" 51 | # the path to the psiblast program executable downloaded as part of the blast program suite 52 | psiblast_executable_path = "/opt/aci/sw/ncbi-rmblastn/2.9/0_gcc-8.3.1-bxy/bin/psiblast" 53 | # prefix of the indexed blast database files created using makeblastdb 54 | blast_db_prefix = "./pssmpro_test_data/uniref50/uniref50db" 55 | # number of cores to be used while creating the pssm profiles 56 | number_of_cores = 8 57 | 58 | 59 | create_pssm_profile(protein_sequence_file, output_dir, psiblast_executable_path, 60 | blast_db_prefix, number_of_cores) 61 | ``` 62 | 63 | ## Generating PSSM features 64 | 65 | *pssmpro* contains 21 features which are capable of numerically encoding protein sequences using their pssm profiles. They are: 66 | 67 | 1. aac_pssm 68 | 2. aadp_pssm 69 | 3. aatp 70 | 4. ab_pssm 71 | 5. d_fpssm 72 | 6. dp_pssm 73 | 7. dpc_pssm 74 | 8. edp 75 | 9. eedp 76 | 10. k_separated_bigrams_pssm 77 | 11. medp 78 | 12. pse_pssm 79 | 13. pssm_ac 80 | 14. pssm_cc 81 | 15. pssm_composition 82 | 16. rpm_pssm 83 | 17. rpssm 84 | 18. s_fpssm 85 | 19. smoothed_pssm 86 | 20. tpc_pssm 87 | 21. tri_gram_pssm 88 | 89 | For a detailed description of the features, refer to the Supplementary Documents of the paper (link to be added). 90 | Other protein sequence encoding 91 | 92 | **NB: *pssmpro* is based on POSSUM [link](https://academic.oup.com/bioinformatics/article/33/17/2756/3813283). The code 93 | has been adapted to work with python version 3 and above.** 94 | 95 | ## similar modules to encode protein sequences 96 | 97 | Other modules that can be used to generate numerical encoding of protein sequences are: 98 | 99 | 1. *ngrampro* [link](https://pypi.org/project/ngrampro/) 100 | 2. *ifeatpro* [link](https://pypi.org/project/ifeatpro/) 101 | 102 | 103 | ```python 104 | # Usage example 105 | 106 | # To create any one of the 21 features one can use the "get_feature" function 107 | 108 | pssm_dir_path = "./pssmpro_test_data/pssm_profiles/" 109 | feature_type = "aac_pssm" 110 | output_dir_path = "./pssmpro_test_data/features/" 111 | 112 | get_feature(pssm_dir_path, feature_type, output_dir_path) 113 | ``` 114 | 115 | 116 | ```python 117 | # To create all 21 features at once, one can use the "get_all_features" function 118 | 119 | get_all_features(pssm_dir_path, output_dit_path) 120 | ``` 121 | -------------------------------------------------------------------------------- /src/pssmpro/features.py: -------------------------------------------------------------------------------- 1 | import re 2 | import os 3 | import numpy as np 4 | import itertools 5 | 6 | # Global Variable, all available encoders 7 | all_encoders = ['aac_pssm', 'aadp_pssm', 'aatp', 'ab_pssm', 'd_fpssm', 'dp_pssm', 'dpc_pssm', 'edp', 'eedp', 8 | 'k_separated_bigrams_pssm', 'medp', 'pse_pssm', 'pssm_ac', 'pssm_cc', 9 | 'pssm_composition', 'rpm_pssm', 'rpssm', 's_fpssm', 'smoothed_pssm', 'tpc_pssm', 'tri_gram_pssm'] 10 | 11 | 12 | # pssm input file reading functions 13 | def read_pssm_matrix(input_matrix): 14 | """ Reading the PSSM input file into a numpy array""" 15 | PSSM = [] 16 | p = re.compile(r'-*[0-9]+') 17 | stream = open(input_matrix) 18 | for line, string in enumerate(stream.readlines()): 19 | if line > 2: 20 | str_vec = [] 21 | overall_vec = string.split() 22 | if len(overall_vec) == 0: 23 | break 24 | str_vec.extend(overall_vec[1]) 25 | 26 | if len(overall_vec) < 44: 27 | for cur_str in overall_vec[2:]: 28 | str_vec.extend(p.findall(cur_str)) 29 | if len(str_vec) >= 21: 30 | if len(str_vec) > 21: 31 | raise ValueError("Wrong PSSM format") 32 | break 33 | print("Done") 34 | else: 35 | str_vec = string.split()[1:42] 36 | if len(str_vec) == 0: 37 | break 38 | PSSM.append(str_vec) 39 | PSSM = np.array(PSSM) 40 | return PSSM 41 | 42 | 43 | # pssm matrix parsing functions 44 | def average(matrix_sum, seq_len): 45 | """average the rows of a pssm""" 46 | matrix_array = np.divide(matrix_sum, seq_len) 47 | matrix_array_shp = np.shape(matrix_array) 48 | matrix_average = [np.reshape(matrix_array, (matrix_array_shp[0] * matrix_array_shp[1],))] 49 | return matrix_average 50 | 51 | 52 | def normalize_pssm(pssm): 53 | """ Normalizing a PSSM """ 54 | pssm = pssm[:, 1:21] 55 | pssm = pssm.astype(float) 56 | 57 | seq_cn = np.shape(pssm)[0] 58 | PSSM_norm = [[0.0] * 20] * seq_cn 59 | PSSM_norm = np.array(PSSM_norm) 60 | mean_matrix = np.mean(pssm, axis=1) 61 | std_matrix = np.std(pssm, axis=1) 62 | 63 | for i in range(seq_cn): 64 | for j in range(20): 65 | if std_matrix[i] == 0.0: 66 | PSSM_norm[i][j] = pssm[i][j] - mean_matrix[i] 67 | else: 68 | PSSM_norm[i][j] = (pssm[i][j] - mean_matrix[i]) / std_matrix[i] 69 | return PSSM_norm 70 | 71 | 72 | def window(pssm, w_smooth, w_slide): 73 | """Smooth PSSM creation""" 74 | # 0-19 represents amino acid 'ARNDCQEGHILKMFPSTWYV' 75 | w_smooth = int(w_smooth) 76 | w_slide = int(w_slide) 77 | 78 | pssm = pssm[:, 1:21] 79 | pssm = pssm.astype(float) 80 | 81 | seq_cn = np.shape(pssm)[0] 82 | 83 | # original PSSM 84 | PSSM_smooth = np.array([[0.0] * 20] * seq_cn) 85 | PSSM_orig = np.array(pssm) 86 | 87 | # section for PSSM_smooth features 88 | PSSM_smooth_full = pssm_smooth(PSSM_orig, PSSM_smooth, w_smooth, seq_cn) 89 | 90 | PSSM_smooth_final = [[0.0] * 20] * w_slide 91 | PSSM_smooth_final = np.array(PSSM_smooth_final) 92 | for i in range(w_slide): 93 | PSSM_smooth_final[i] = PSSM_smooth_full[i] 94 | matrix_final = average(PSSM_smooth_final, 1.0) 95 | return matrix_final 96 | 97 | 98 | def pssm_smooth(pssm_original, pssm_smooth_new, w_smooth, seq_len): 99 | """Smooth PSSM creation helper""" 100 | for i in range(seq_len): 101 | if i < (w_smooth - 1) / 2: 102 | for j in range(i + (w_smooth - 1) // 2 + 1): 103 | pssm_smooth_new[i] += pssm_original[j] 104 | elif i >= (seq_len - (w_smooth - 1) // 2): 105 | for j in range(i - (w_smooth - 1) // 2, seq_len): 106 | pssm_smooth_new[i] += pssm_original[j] 107 | else: 108 | for j in range(i - (w_smooth - 1) // 2, i + (w_smooth - 1) // 2 + 1): 109 | pssm_smooth_new[i] += pssm_original[j] 110 | return pssm_smooth_new 111 | 112 | 113 | def handle_rows(pssm, switch, count): 114 | """ 115 | if SWITCH=0, we filter no element. 116 | if SWITCH=1, we filter all the negative elements. 117 | if SWITCH=2, we filter all the negative and positive elements greater than expected. 118 | if COUNT=20, we generate a 20-dimension vector. 119 | if COUNT=400, we generate a 400-dimension vector. 120 | 121 | Convert the PSSM matrix into sum of their rows either by taking the amino acids or not taking them into account 122 | """ 123 | # 0-19 represents amino acid 'ARNDCQEGHILKMFPSTWYV' 124 | Amino_vec = "ARNDCQEGHILKMFPSTWYV" 125 | 126 | matrix_final = [[0.0] * 20] * int(count / 20) 127 | matrix_final = np.array(matrix_final) 128 | seq_cn = 0 129 | 130 | PSSM_shape = np.shape(pssm) 131 | for i in range(PSSM_shape[0]): 132 | seq_cn += 1 133 | str_vec = pssm[i] 134 | str_vec_positive = list(map(int, str_vec[1:21])) 135 | str_vec_positive = np.array(str_vec_positive) 136 | if switch == 1: 137 | str_vec_positive[str_vec_positive < 0] = 0 138 | elif switch == 2: 139 | str_vec_positive[str_vec_positive < 0] = 0 140 | str_vec_positive[str_vec_positive > 7] = 0 141 | if count == 20: 142 | matrix_final[0] = list(map(sum, zip(str_vec_positive, matrix_final[0]))) 143 | elif count == 400: 144 | matrix_final[Amino_vec.index(str_vec[0])] = list(map(sum, zip(str_vec_positive, 145 | matrix_final[Amino_vec.index(str_vec[0])]))) 146 | 147 | return matrix_final 148 | 149 | 150 | def pre_handle_columns(pssm, step, part, idx): 151 | """ 152 | if step=k, we calculate the relation between one residue and the kth residue afterward. 153 | 154 | if part=0, we calculate the left part of PSSM. 155 | if part=1, we calculate the right part of PSSM. 156 | 157 | if idx=0, we product the residue-pair. 158 | if idx=1, we minus the residue-pair. 159 | 160 | if key=1, we divide each element by the sum of elements in its column. 161 | if key=0, we don't perform the above process. 162 | 163 | Preprocessing the PSSM column-wise 164 | """ 165 | 166 | if part == 0: 167 | pssm = pssm[:, 1:21] 168 | elif part == 1: 169 | pssm = pssm[:, 21:] 170 | pssm = pssm.astype(float) 171 | matrix_final = [[0.0] * 20] * 20 172 | matrix_final = np.array(matrix_final) 173 | seq_cn = np.shape(pssm)[0] 174 | 175 | if idx == 0: 176 | for i in range(20): 177 | for j in range(20): 178 | for k in range(seq_cn - step): 179 | matrix_final[i][j] += (pssm[k][i] * pssm[k + step][j]) 180 | 181 | elif idx == 1: 182 | for i in range(20): 183 | for j in range(20): 184 | for k in range(seq_cn - step): 185 | matrix_final[i][j] += ((pssm[k][i] - pssm[k + step][j]) * (pssm[k][i] - pssm[k + step][j]) / 4.0) 186 | 187 | return matrix_final 188 | 189 | 190 | def handle_tri_columns(pssm): 191 | """ 192 | Preprocessing three columns of a PSSM 193 | """ 194 | matrix_final = [[[0.0] * 20] * 20] * 20 195 | matrix_final = np.array(matrix_final) 196 | pssm = pssm[:, 21:] 197 | pssm = pssm.astype(float) 198 | pssm = np.array(pssm) 199 | 200 | seq_cn = np.shape(pssm)[0] 201 | for m in range(20): 202 | for n in range(20): 203 | for r in range(20): 204 | for i in range(seq_cn - 2): 205 | matrix_final[m][n][r] += (pssm[i, m] * pssm[i + 1, n] * pssm[i + 2, r]) 206 | 207 | matrix_final = np.divide(matrix_final, 1000000.0) 208 | matrix_final_shape = np.shape(matrix_final) 209 | 210 | matrix_result = [ 211 | (np.reshape(matrix_final, (matrix_final_shape[0] * matrix_final_shape[1] * matrix_final_shape[2],)))] 212 | return matrix_result 213 | 214 | 215 | def handle_mixed(pssm, alpha): 216 | """ 217 | preprocessing PSSM mixed 218 | """ 219 | row1 = [0.0] * 20 220 | row2 = [0.0] * 20 221 | 222 | matrix_final = [[0.0] * 40] * 1 223 | row1 = np.array(row1) 224 | row2 = np.array(row2) 225 | matrix_final = np.array(matrix_final) 226 | 227 | pssm_norm = normalize_pssm(pssm) 228 | seq_cn = np.shape(pssm)[0] 229 | for i in range(seq_cn): 230 | row1 = list(map(sum, zip(row1, pssm_norm[i]))) 231 | 232 | row1 = np.divide(row1, seq_cn) 233 | 234 | for j in range(20): 235 | for i in range(seq_cn - alpha): 236 | row2[j] += (pssm_norm[i][j] - pssm_norm[i + alpha][j]) * (pssm_norm[i][j] - pssm_norm[i + alpha][j]) 237 | 238 | row2 = np.divide(row2, seq_cn - alpha) 239 | 240 | row = np.hstack((row1, row2)) 241 | matrix_final[0] = row 242 | return matrix_final 243 | 244 | 245 | def handle_mixed2(pssm, alpha): 246 | """ 247 | preprocessing PSSM mixed2 248 | :param pssm: 249 | :param alpha: 250 | :return: 251 | """ 252 | row1 = [0.0] * 40 253 | row2 = [[0.0] * (2 * alpha)] * 20 254 | matrix_final = [[0.0] * (40 + 40 * alpha)] * 1 255 | 256 | row1 = np.array(row1) 257 | row2 = np.array(row2) 258 | matrix_final = np.array(matrix_final) 259 | 260 | pssm_norm = normalize_pssm(pssm) 261 | seq_cn = np.shape(pssm)[0] 262 | for j in range(20): 263 | positive_count_1 = 0 264 | negative_count_1 = 0 265 | for i in range(seq_cn): 266 | if pssm_norm[i][j] >= 0: 267 | positive_count_1 += 1 268 | row1[2 * j] += pssm_norm[i][j] 269 | elif pssm_norm[i][j] < 0: 270 | 271 | negative_count_1 += 1 272 | row1[2 * j + 1] += pssm_norm[i][j] 273 | 274 | row1[2 * j] = row1[2 * j] / positive_count_1 275 | row1[2 * j + 1] = row1[2 * j + 1] / negative_count_1 276 | 277 | for j in range(20): 278 | for alpha in range(1, alpha + 1): 279 | positive_count_2 = 0 280 | negative_count_2 = 0 281 | for i in range(seq_cn - alpha): 282 | if (pssm_norm[i][j] - pssm_norm[i + alpha][j]) >= 0: 283 | positive_count_2 += 1 284 | row2[j][2 * alpha - 2] += (pssm_norm[i][j] - pssm_norm[i + alpha][j]) * ( 285 | pssm_norm[i][j] - pssm_norm[i + alpha][j]) 286 | elif (pssm_norm[i][j] - pssm_norm[i + alpha][j]) < 0: 287 | negative_count_2 += 1 288 | row2[j][2 * alpha - 1] += (pssm_norm[i][j] - pssm_norm[i + alpha][j]) * ( 289 | pssm_norm[i][j] - pssm_norm[i + alpha][j]) 290 | row2[j][2 * alpha - 2] = row2[j][2 * alpha - 2] / positive_count_2 291 | row2[j][2 * alpha - 1] = row2[j][2 * alpha - 1] / negative_count_2 292 | 293 | row2 = average(row2, 1.0) 294 | row = np.hstack((row1, row2[0])) 295 | matrix_final[0] = row 296 | return matrix_final 297 | 298 | 299 | def handle_mixed3(pssm): 300 | """ 301 | preprocessing PSSM mixed3 302 | """ 303 | row = [[0.0] * 110] * 1 304 | # row1 = [0.0] * 100 305 | row2 = [0.0] * 10 306 | row = np.array(row) 307 | row2 = np.array(row2) 308 | 309 | seq_cn = np.shape(pssm)[0] 310 | r_pssm = [[0.0] * 10] * seq_cn 311 | r_pssm = np.array(r_pssm) 312 | 313 | pssm = pssm[:, 1:21] 314 | pssm = pssm.astype(float) 315 | pssm = np.array(pssm) 316 | 317 | r_pssm[:, 0] = np.divide(list(map(sum, zip(pssm[:, 13], pssm[:, 17], pssm[:, 18]))), 3.0) 318 | r_pssm[:, 1] = np.divide(list(map(sum, zip(pssm[:, 10], pssm[:, 12]))), 2.0) 319 | r_pssm[:, 2] = np.divide(list(map(sum, zip(pssm[:, 9], pssm[:, 19]))), 2.0) 320 | r_pssm[:, 3] = np.divide(list(map(sum, zip(pssm[:, 0], pssm[:, 15], pssm[:, 16]))), 3.0) 321 | r_pssm[:, 4] = np.divide(list(map(sum, zip(pssm[:, 2], pssm[:, 8]))), 2.0) 322 | r_pssm[:, 5] = np.divide(list(map(sum, zip(pssm[:, 5], pssm[:, 6], pssm[:, 3]))), 3.0) 323 | r_pssm[:, 6] = np.divide(list(map(sum, zip(pssm[:, 1], pssm[:, 11]))), 2.0) 324 | r_pssm[:, 7] = pssm[:, 4] 325 | r_pssm[:, 8] = pssm[:, 7] 326 | r_pssm[:, 9] = pssm[:, 14] 327 | 328 | mean_matrix = np.mean(r_pssm, axis=0) 329 | 330 | for j in range(10): 331 | for i in range(seq_cn): 332 | row2[j] += (r_pssm[i][j] - mean_matrix[j]) * (r_pssm[i][j] - mean_matrix[j]) 333 | 334 | row2 = np.divide(row2, seq_cn) 335 | matrix_final = [[0.0] * 10] * 10 336 | matrix_final = np.array(matrix_final) 337 | for i in range(10): 338 | for j in range(10): 339 | for k in range(seq_cn - 1): 340 | matrix_final[i][j] += ((r_pssm[k][i] - r_pssm[k + 1][j]) * (r_pssm[k][i] - r_pssm[k + 1][j]) / 2.0) 341 | 342 | row1 = average(matrix_final, seq_cn - 1)[0] 343 | row[0] = np.hstack((row1, row2)) 344 | return row 345 | 346 | 347 | def correlation(pssm, idx, group): 348 | """ 349 | PSSM correlation calculator 350 | :param pssm: 351 | :param idx: 352 | :param group: 353 | :return: 354 | """ 355 | # 0-19 represents amino acid 'ARNDCQEGHILKMFPSTWYV' 356 | # GROUP=10 357 | pssm = pssm[:, 1:21] 358 | pssm = pssm.astype(float) 359 | 360 | # section for PSSM_AC features 361 | seq_cn = np.shape(pssm)[0] 362 | g = group 363 | seq_len = seq_cn 364 | if idx == 0: 365 | matrix_final = pssm_ac_cal(pssm, g, seq_len) 366 | elif idx == 1: 367 | matrix_final = pssm_cc_cal(pssm, g, seq_len) 368 | else: 369 | raise ValueError("Wrong idx assigned") 370 | 371 | matrix_final = average(matrix_final, seq_len) 372 | return matrix_final 373 | 374 | 375 | def pssm_ac_cal(pssm, g, seq_len): 376 | """ 377 | PSSM AC helper 378 | :param pssm: 379 | :param g: 380 | :param seq_len: 381 | :return: 382 | """ 383 | pssm_ac_matrix = np.array([[0.0] * 20] * g) 384 | 385 | for pg in range(g): 386 | l_g = seq_len - pg - 1 387 | for pj in range(20): 388 | sum_jl = 0.0 389 | for i in range(seq_len): 390 | sum_jl += pssm[i][pj] 391 | sum_jl /= seq_len 392 | 393 | pssm_acjg = 0.0 394 | for i in range(l_g): 395 | pssm_acjg += (pssm[i][pj] - sum_jl) * (pssm[i + pg + 1][pj] - sum_jl) 396 | pssm_acjg /= l_g 397 | pssm_ac_matrix[pg][pj] = pssm_acjg 398 | return pssm_ac_matrix 399 | 400 | 401 | def pssm_cc_cal(pssm, g, seq_len): 402 | """ 403 | PSSM CC helper 404 | :param pssm: 405 | :param g: 406 | :param seq_len: 407 | :return: 408 | """ 409 | PSSM_CC = np.array([[0.0] * 380] * g) 410 | for pg in range(g): 411 | l_g = seq_len - pg - 1 412 | for pj_1 in range(20): 413 | sum_jl_1 = 0.0 414 | for i in range(seq_len): 415 | sum_jl_1 += pssm[i][pj_1] 416 | sum_jl_1 /= seq_len 417 | 418 | for pj_2 in range(20): 419 | if pj_2 != pj_1: 420 | sum_jl_2 = 0.0 421 | for i in range(seq_len): 422 | sum_jl_2 += pssm[i][pj_2] 423 | sum_jl_2 /= seq_len 424 | pssm_acjg = 0.0 425 | for i in range(l_g): 426 | pssm_acjg += (pssm[i][pj_1] - sum_jl_1) * (pssm[i + pg + 1][pj_2] - sum_jl_2) 427 | pssm_acjg /= l_g 428 | if pj_1 < pj_2: 429 | PSSM_CC[pg][19 * pj_1 + (pj_2 - 1)] = pssm_acjg 430 | else: 431 | PSSM_CC[pg][19 * pj_1 + pj_2] = pssm_acjg 432 | 433 | return PSSM_CC 434 | 435 | 436 | # Actual functions of encoders 437 | # row transformation based feature encoding algorithms 438 | def aac_pssm(input_matrix): 439 | """ 440 | AAC PSSM feature encoder 441 | :param input_matrix: 442 | :return: 443 | """ 444 | SWITCH = 0 445 | COUNT = 20 446 | seq_cn = float(np.shape(input_matrix)[0]) 447 | aac_pssm_matrix = handle_rows(input_matrix, SWITCH, COUNT) 448 | aac_pssm_matrix = np.array(aac_pssm_matrix) 449 | aac_pssm_vector = average(aac_pssm_matrix, seq_cn) 450 | return aac_pssm_vector[0] 451 | 452 | 453 | def d_fpssm(input_matrix): 454 | """ 455 | D FPSSM feature encoder 456 | :param input_matrix: 457 | :return: 458 | """ 459 | SWITCH = 1 460 | COUNT = 20 461 | d_fpssm_matrix = handle_rows(input_matrix, SWITCH, COUNT) 462 | seqLen = float(np.shape(input_matrix)[0]) 463 | seq_cn = 1.0 464 | element_max = np.amax(d_fpssm_matrix[0], axis=0) 465 | element_min = np.amin(d_fpssm_matrix[0], axis=0) 466 | d_fpssm_vector = average(d_fpssm_matrix, seq_cn) 467 | d_fpssm_vector = np.add(d_fpssm_vector, -element_min) 468 | d_fpssm_vector = np.divide(d_fpssm_vector, element_max) 469 | d_fpssm_vector = np.divide(d_fpssm_vector, seqLen) 470 | return d_fpssm_vector[0] 471 | 472 | 473 | def smoothed_pssm(input_matrix, smooth=7, slide=50): 474 | """ 475 | Smoothed PSSM feature encoder 476 | :param input_matrix: 477 | :param smooth: 478 | :param slide: 479 | :return: 480 | """ 481 | smoothed_pssm_matrix = window(input_matrix, smooth, slide) 482 | return smoothed_pssm_matrix[0] 483 | 484 | 485 | def ab_pssm(input_matrix): 486 | """ 487 | AB PSSM feature encoder 488 | :param input_matrix: 489 | :return: 490 | """ 491 | seq_cn = np.shape(input_matrix)[0] 492 | BLOCK = int(seq_cn/20) 493 | 494 | matrix_final = [] 495 | for i in range(19): 496 | tmp = input_matrix[i*BLOCK:(i+1)*BLOCK] 497 | matrix_final.append(aac_pssm(tmp)) 498 | tmp = input_matrix[19*BLOCK:] 499 | matrix_final.append(aac_pssm(tmp)) 500 | ab_pssm_matrix = average(matrix_final, 1.0) 501 | return ab_pssm_matrix[0] 502 | 503 | 504 | def pssm_composition(input_matrix): 505 | """ 506 | PSSM composition feature encoder 507 | :param input_matrix: 508 | :return: 509 | """ 510 | SWITCH = 0 511 | COUNT = 400 512 | seq_cn = float(np.shape(input_matrix)[0]) 513 | pssm_composition_matrix = handle_rows(input_matrix, SWITCH, COUNT) 514 | pssm_composition_vector = average(pssm_composition_matrix, seq_cn) 515 | return pssm_composition_vector[0] 516 | 517 | 518 | def rpm_pssm(input_matrix): 519 | """ 520 | RPM PSSM feature encoder 521 | :param input_matrix: 522 | :return: 523 | """ 524 | SWITCH = 1 525 | COUNT = 400 526 | seq_cn = float(np.shape(input_matrix)[0]) 527 | rpm_pssm_matrix = handle_rows(input_matrix, SWITCH, COUNT) 528 | rpm_pssm_vector = average(rpm_pssm_matrix, seq_cn) 529 | return rpm_pssm_vector[0] 530 | 531 | 532 | def s_fpssm(input_matrix): 533 | """ 534 | S FPSSM feature encoder 535 | :param input_matrix: 536 | :return: 537 | """ 538 | SWITCH = 2 539 | COUNT = 400 540 | s_fpssm_matrix = handle_rows(input_matrix, SWITCH, COUNT) 541 | s_fpssm_matrix = np.array(s_fpssm_matrix) 542 | s_fpssm_matrix_shape = np.shape(s_fpssm_matrix) 543 | matrix_average = [(np.reshape(s_fpssm_matrix, (s_fpssm_matrix_shape[0] * s_fpssm_matrix_shape[1], )))] 544 | return matrix_average[0] 545 | 546 | 547 | # column transformation based feature encoders 548 | def dpc_pssm(input_matrix): 549 | """ 550 | DPC PSSM feature encoder 551 | :param input_matrix: 552 | :return: 553 | """ 554 | PART = 0 555 | STEP = 1 556 | ID = 0 557 | matrix_final = pre_handle_columns(input_matrix, STEP, PART, ID) 558 | seq_cn = float(np.shape(input_matrix)[0]) 559 | dpc_pssm_vector = average(matrix_final, seq_cn-STEP) 560 | return dpc_pssm_vector[0] 561 | 562 | 563 | def k_separated_bigrams_pssm(input_matrix, step=1): 564 | """ 565 | k separated bigrams feature encoder 566 | :param input_matrix: 567 | :param step: 568 | :return: 569 | """ 570 | PART = 1 571 | ID = 0 572 | matrix_final = pre_handle_columns(input_matrix, step, PART, ID) 573 | k_separated_bigrams_pssm_vector = average(matrix_final, 10000.0) 574 | return k_separated_bigrams_pssm_vector[0] 575 | 576 | 577 | def tri_gram_pssm(input_matrix): 578 | """ 579 | Tri gram PSSM feature encoder 580 | :param input_matrix: 581 | :return: 582 | """ 583 | tri_gram_pssm_matrix = handle_tri_columns(input_matrix) 584 | return tri_gram_pssm_matrix[0] 585 | 586 | 587 | def eedp(input_matrix): 588 | """ 589 | EEDP feature encoder 590 | :param input_matrix: 591 | :return: 592 | """ 593 | STEP = 2 594 | PART = 0 595 | ID = 1 596 | seq_cn = float(np.shape(input_matrix)[0]) 597 | matrix_final = pre_handle_columns(input_matrix, STEP, PART, ID) 598 | eedp_vector = average(matrix_final, seq_cn-STEP) 599 | return eedp_vector[0] 600 | 601 | 602 | def tpc_pssm(input_matrix): 603 | """ 604 | TPC feature encoder 605 | :param input_matrix: 606 | :return: 607 | """ 608 | PART = 0 609 | STEP = 1 610 | ID = 0 611 | matrix_final = pre_handle_columns(input_matrix, STEP, PART, ID) 612 | matrix_tmp = [0.0] * 20 613 | matrix_tmp = np.array(matrix_tmp) 614 | for i in range(20): 615 | matrix_tmp = list(map(sum, zip(matrix_final[i], matrix_tmp))) 616 | for i in range(20): 617 | for j in range(20): 618 | matrix_final[i][j] = matrix_final[i][j]/matrix_tmp[j] 619 | tpc_vector = average(matrix_final, 1.0) 620 | return tpc_vector[0] 621 | 622 | 623 | # Mixture of row and column transformation based feature encoders 624 | def edp(input_matrix): 625 | """ 626 | EDP feature encoder 627 | :param input_matrix: 628 | :return: 629 | """ 630 | STEP = 2 631 | PART = 0 632 | ID = 1 633 | edp_matrix = [[0.0] * 20] * 1 634 | edp_matrix = np.array(edp_matrix) 635 | seq_cn = float(np.shape(input_matrix)[0]) 636 | output_matrix = pre_handle_columns(input_matrix, STEP, PART, ID) 637 | output_matrix = np.array(output_matrix) 638 | for i in range(20): 639 | edp_matrix[0] = list(map(sum, zip(output_matrix[i], edp_matrix[0]))) 640 | edp_matrix = np.divide(edp_matrix, (seq_cn-STEP)*20.0) 641 | return edp_matrix[0] 642 | 643 | 644 | def rpssm(input_matrix): 645 | """ 646 | RPSSM feature encoder 647 | :param input_matrix: 648 | :return: 649 | """ 650 | rpssm_matrix = handle_mixed3(input_matrix) 651 | return rpssm_matrix[0] 652 | 653 | 654 | def pse_pssm(input_matrix, alpha=1): 655 | """ 656 | PSE PSSM feature encoder 657 | :param input_matrix: 658 | :param alpha: 659 | :return: 660 | """ 661 | pse_pssm_matrix = handle_mixed(input_matrix, alpha) 662 | return pse_pssm_matrix[0] 663 | 664 | 665 | def dp_pssm(input_matrix, alpha=5): 666 | """ 667 | DP PSSM feature encoder 668 | :param input_matrix: 669 | :param alpha: 670 | :return: 671 | """ 672 | dp_pssm_matrix = handle_mixed2(input_matrix, alpha) 673 | return dp_pssm_matrix[0] 674 | 675 | 676 | def pssm_ac(input_matrix, group=10): 677 | """ 678 | PSSM AC feature encoder 679 | :param input_matrix: 680 | :param group: 681 | :return: 682 | """ 683 | ID = 0 684 | pssm_ac_matrix = correlation(input_matrix, ID, group) 685 | return pssm_ac_matrix[0] 686 | 687 | 688 | def pssm_cc(input_matrix, group=10): 689 | """ 690 | PSSM CC feature encoder 691 | :param input_matrix: 692 | :param group: 693 | :return: 694 | """ 695 | ID = 1 696 | pssm_cc_matrix = correlation(input_matrix, ID, group) 697 | return pssm_cc_matrix[0] 698 | 699 | 700 | # Feature encoding algorithms that combine the above encoders 701 | def aadp_pssm(input_matrix): 702 | """ 703 | aac and dpc combined encoder 704 | :param input_matrix: 705 | :return: 706 | """ 707 | aac_pssm_matrix = aac_pssm(input_matrix) 708 | dpc_pssm_matrix = dpc_pssm(input_matrix) 709 | aac_pssm_matrix = np.array(aac_pssm_matrix) 710 | dpc_pssm_matrix = np.array(dpc_pssm_matrix) 711 | aadp_pssm_matrix = np.hstack((aac_pssm_matrix, dpc_pssm_matrix)) 712 | return aadp_pssm_matrix 713 | 714 | 715 | def aatp(input_matrix): 716 | """ 717 | aac and tpc combined encoder 718 | :param input_matrix: 719 | :return: 720 | """ 721 | aac_pssm_matrix = aac_pssm(input_matrix) 722 | tpc_matrix = tpc_pssm(input_matrix) 723 | aac_pssm_matrix = np.array(aac_pssm_matrix) 724 | tpc_matrix = np.array(tpc_matrix) 725 | aatp_matrix = np.hstack((aac_pssm_matrix, tpc_matrix)) 726 | return aatp_matrix 727 | 728 | 729 | def medp(input_matrix): 730 | """ 731 | edp and eedp combined encoder 732 | :param input_matrix: 733 | :return: 734 | """ 735 | edp_matrix = edp(input_matrix) 736 | eedp_matrix = eedp(input_matrix) 737 | edp_matrix = np.array(edp_matrix) 738 | eedp_matrix = np.array(eedp_matrix) 739 | medp_matrix = np.hstack((edp_matrix, eedp_matrix)) 740 | return medp_matrix 741 | 742 | 743 | def get_feature(pssm_dir, algo_type="aac_pssm", store_dir="./"): 744 | pssm_files = [os.path.join(pssm_dir, pf.name) for pf in os.scandir(pssm_dir) if pf.name.endswith(".pssm")] 745 | pssm_mat = list(map(read_pssm_matrix, pssm_files)) 746 | features = np.array(list(map(eval(algo_type), pssm_mat))) 747 | 748 | protein_names = [re.sub(".pssm", "", pf.name) for pf in os.scandir(pssm_dir) if pf.name.endswith(".pssm")] 749 | 750 | if store_dir: 751 | os.makedirs(store_dir, exist_ok=True) 752 | with open(os.path.join(store_dir, algo_type+".csv"), "w") as f: 753 | for pn, feats in zip(protein_names, features): 754 | f.write(pn + ",") 755 | f.write(",".join(list(map(str, feats)))) 756 | f.write("\n") 757 | return algo_type 758 | else: 759 | return zip(protein_names, features) 760 | 761 | 762 | def get_all_features(pssm_dir, store_dir="./"): 763 | if store_dir: 764 | algo_types = [get_feature(pssm_dir, enc, store_dir) for enc in all_encoders] 765 | return algo_types 766 | else: 767 | return [get_feature(pssm_dir, enc, store_dir) for enc in all_encoders] 768 | 769 | 770 | # create pssm profile function 771 | def create_pssm_profile(seq_file, out_dir, psiblast_exec, database_prefix, num_threads=24): 772 | """ 773 | A function to create psiblast or pssm profile for protein sequences 774 | :param seq_file: A csv file with name of the protein followed by its sequence separated by a comma 775 | :param out_dir: The directory where the user would like to store the pssm profiles of all the sequences 776 | :param psiblast_exec: The path of the psiblast executable. psiblast program needs to be installed 777 | :param database_prefix: The path of the indexed blast database directory prefix 778 | :param num_threads: Number of threads to use while creating the psiblast profile 779 | :return: The output directory where the psiblast/pssm profiles are stored 780 | """ 781 | 782 | os.makedirs(out_dir, exist_ok=True) 783 | 784 | for line in open(seq_file).readlines(): 785 | parsed_line = line.strip().split(",") 786 | name, sequence = parsed_line[0], parsed_line[1] 787 | with open(name + '.txt', 'w') as f: 788 | f.write('>' + name + '\n' + sequence + '\n') 789 | myCmd = f"{psiblast_exec} -query {name}.txt -db {database_prefix} -num_iterations 3 -num_threads " \ 790 | f"{num_threads} -out_ascii_pssm {os.path.join(out_dir, name + '.pssm')}" 791 | print("Generating psiblast profile for protein: " + name) 792 | os.system(myCmd) 793 | os.remove(name + '.txt') 794 | return out_dir 795 | 796 | 797 | if __name__ == "__main__": 798 | zip_list = get_all_features("./data/pssm_files", store_dir="./data/tmp") 799 | print(list(zip_list[0])) 800 | -------------------------------------------------------------------------------- /src/pssmpro/data/pssm_files/example_2.pssm: -------------------------------------------------------------------------------- 1 | 2 | Last position-specific scoring matrix computed, weighted observed percentages rounded down, information per position, and relative weight of gapless real matches to pseudocounts 3 | A R N D C Q E G H I L K M F P S T W Y V A R N D C Q E G H I L K M F P S T W Y V 4 | 1 M -1 -1 -2 -3 -2 0 -2 -3 -2 1 2 -1 6 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0.34 0.00 5 | 2 H -1 0 0 -1 -3 4 1 -2 7 -3 -3 0 -1 -2 -2 -1 -1 -2 1 -3 0 0 0 0 0 39 0 0 61 0 0 0 0 0 0 0 0 0 0 0 0.60 0.00 6 | 3 I 1 -3 -3 -3 -1 -2 -3 -3 -3 3 1 -2 1 -1 -2 -1 0 -3 -2 3 20 0 0 0 0 0 0 0 0 55 0 0 0 0 0 0 0 0 0 25 0.24 0.00 7 | 4 M -1 -2 -2 -3 -2 -1 -2 -3 -2 1 2 -2 6 2 0 -2 0 -1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 78 10 6 0 6 0 0 0 0.34 0.02 8 | 5 P 0 -2 1 -1 -3 -1 -1 -2 1 -3 -3 -1 -3 -4 7 -1 -1 -4 -3 -3 7 0 10 0 0 0 0 0 5 0 0 0 0 0 78 0 0 0 0 0 1.48 0.02 9 | 6 P 1 -2 -1 -1 -2 -1 -1 -1 -2 -2 0 -1 -1 -2 5 2 0 -3 -2 -1 14 0 0 0 0 0 0 0 0 0 14 0 0 0 40 31 0 0 0 0 0.63 0.01 10 | 7 E 0 -1 -1 1 -3 1 3 -2 1 -3 -3 0 -2 -3 5 0 1 -3 -2 -2 5 0 0 4 0 6 31 0 6 0 0 0 0 0 35 0 13 0 0 0 0.63 0.01 11 | 8 I 0 2 -1 -2 -2 -1 -1 -2 0 1 0 0 0 -2 -2 0 3 -3 -1 0 3 18 0 0 0 0 0 0 4 23 4 0 0 0 0 4 43 0 0 0 0.17 0.01 12 | 9 A 0 -1 -2 -2 2 -1 -1 -2 1 -2 -1 -1 -2 -1 6 0 -1 -3 -2 -2 9 4 0 0 6 0 0 0 5 0 7 0 0 5 59 4 0 0 0 0 0.95 0.02 13 | 10 N -1 0 4 2 -3 1 1 -1 1 -1 -1 0 -1 -2 0 1 0 -3 -2 -2 0 4 38 8 0 4 13 0 4 6 9 0 0 0 3 11 0 0 0 0 0.24 0.01 14 | 11 T 0 -2 -1 0 -2 0 -1 -1 0 1 0 -1 0 -1 2 1 2 -3 0 0 3 0 0 5 0 3 0 4 4 20 5 0 0 0 11 15 28 0 3 0 0.14 0.01 15 | 12 M -1 -1 -3 -3 -2 -1 -2 -3 -2 1 2 -2 6 0 0 -2 -1 2 -1 1 4 2 0 0 0 2 0 0 0 0 8 0 66 2 5 0 2 3 0 7 0.40 0.06 16 | 13 S 1 -1 1 0 -2 0 1 -1 0 -1 -1 0 -1 -2 -1 3 1 -3 -2 -1 10 2 9 2 0 2 12 0 2 3 5 0 1 2 2 42 7 0 0 0 0.21 0.02 17 | 14 T 0 0 1 -1 -2 0 0 -1 -1 -1 0 2 1 -2 1 1 2 -3 -2 -1 3 2 6 0 0 0 5 2 0 2 9 22 6 0 5 15 24 0 0 0 0.15 0.02 18 | 15 Q 0 1 1 0 -1 2 0 -1 -1 -2 -1 1 0 -2 1 1 1 -2 -1 -1 8 10 9 3 2 19 0 0 0 0 4 3 7 0 6 19 7 0 1 0 0.16 0.01 19 | 16 P 0 0 0 -1 -2 1 0 -2 -1 -1 -1 0 2 -2 5 0 0 -3 -2 -1 5 3 4 0 0 9 3 0 0 0 3 7 14 0 36 8 5 0 0 2 0.49 0.02 20 | 17 A 2 2 -1 -1 -1 0 -1 -1 -1 -2 -2 1 -1 -2 0 2 2 -3 -2 -1 23 14 0 0 0 4 1 1 1 0 1 7 1 0 4 19 20 0 0 2 0.21 0.03 21 | 18 S 0 -1 1 2 -2 2 0 -1 -1 -2 -3 0 -2 -3 3 1 2 -3 -2 -2 4 1 6 17 1 20 2 1 0 1 0 4 0 0 15 10 18 0 0 0 0.34 0.04 22 | 19 T -2 -3 -2 -3 0 -3 -3 -3 0 -1 -1 -3 -1 6 -2 -2 0 1 5 -1 1 0 2 1 3 0 0 0 1 1 1 0 0 49 1 0 7 0 33 1 0.71 0.09 23 | 20 R -2 5 -2 -3 -2 0 -2 -3 1 0 2 0 0 -1 -3 -2 -2 -1 -2 -1 0 48 0 0 0 1 0 0 4 1 40 1 0 1 0 0 0 1 0 2 0.40 0.07 24 | 21 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 1 -1 -4 -3 -2 -3 -2 2 0 0 0 0 0 0 0 0 0 96 4 0 0 0 0 0 0 0 0 0 0.83 0.12 25 | 22 A 5 -2 -2 -3 -1 -2 -2 -1 -2 -2 -2 -2 -2 -3 -2 1 0 -3 -3 -1 97 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0.75 0.12 26 | 23 P -2 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.43 0.16 27 | 24 S 0 -2 0 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 -2 6 1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.87 0.14 28 | 25 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 1 -1 -4 -3 -2 -3 -2 2 0 0 0 0 0 0 0 0 0 95 5 0 0 0 0 0 0 0 0 0 0.81 0.12 29 | 26 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 1 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.80 0.11 30 | 27 S 1 -2 0 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 -2 6 1 -4 -3 -3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 97 0 0 0 0 0.82 0.13 31 | 28 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.80 0.12 32 | 29 D -3 -2 2 7 -4 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 7 93 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.31 0.13 33 | 30 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -2 0 0 0 0 0 0 0 0 0 0 5 0 0 95 0 0 0 0 0 0 1.28 0.14 34 | 31 A 5 -2 -2 -2 -1 -2 -2 -1 -2 -2 -2 -1 -2 -3 -2 1 -1 -3 -3 -1 94 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0.72 0.11 35 | 32 R -2 7 -1 -2 -1 0 -1 -3 -1 -3 -3 2 -2 -4 -3 -2 -2 -4 -3 -3 1 90 0 0 2 1 1 0 0 1 0 5 0 0 0 0 0 0 0 0 1.09 0.12 36 | 33 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 1 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.80 0.11 37 | 34 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 38 | 35 E -2 -1 -1 2 -5 2 6 -3 -1 -4 -4 0 -3 -4 -2 -1 -2 -4 -3 -3 0 0 1 9 0 4 86 0 0 0 0 0 0 0 0 1 0 0 0 0 0.99 0.12 39 | 36 E -2 -1 0 4 -5 1 5 -3 -1 -4 -4 0 -3 -4 -2 -1 -2 -4 -3 -4 0 0 0 28 0 0 72 0 0 0 0 0 0 0 0 0 0 0 0 0 0.95 0.11 40 | 37 V -1 -3 -3 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 1 -4 -2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 88 0.62 0.11 41 | 38 R 1 4 -1 2 -2 1 2 -2 -1 -3 -3 2 -2 -3 -2 0 0 -3 -2 -2 18 37 0 13 1 3 13 0 1 1 0 8 0 0 0 2 3 0 0 1 0.34 0.05 42 | 39 N 0 1 5 1 -3 1 0 -1 0 -4 -4 2 -2 -4 -2 0 -1 -4 -3 -3 9 10 55 6 0 3 0 0 0 0 0 13 0 0 0 2 1 0 0 0 0.54 0.07 43 | 40 V 0 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 -1 -4 -2 5 4 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 94 0.70 0.11 44 | 41 V -1 -3 -4 -4 -2 -3 -2 -4 -3 3 3 -3 1 0 -3 -2 -1 -3 -2 3 1 0 0 0 0 0 2 0 0 23 45 0 0 0 0 1 2 0 0 26 0.40 0.06 45 | 42 A 4 -1 0 0 -1 0 0 -1 -1 -2 -2 0 -2 -3 -2 1 0 -3 -2 -1 69 1 3 5 0 1 7 0 1 0 0 7 0 0 0 4 2 0 0 0 0.39 0.07 46 | 43 A 5 -2 -2 -2 0 -2 -2 0 -2 -2 -2 -1 -2 -3 -2 1 -1 -3 -3 -1 91 0 0 2 1 0 0 1 0 0 0 0 0 0 0 5 0 0 0 0 0.68 0.11 47 | 44 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 48 | 45 A 5 -2 -2 -3 -1 -2 -2 0 -2 -2 -2 -2 -2 -3 -2 1 -1 -3 -3 -1 95 0 0 0 0 0 0 4 0 0 0 0 0 0 0 1 1 0 0 0 0.72 0.11 49 | 46 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 98 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1.40 0.14 50 | 47 W -2 -3 -4 -4 -2 -3 -4 -4 -4 3 1 -3 1 0 -4 -3 -2 8 0 3 0 0 0 0 0 0 0 0 0 19 10 0 2 1 0 0 0 33 0 36 0.83 0.09 51 | 48 I -1 -4 -4 -4 -2 -3 -4 -4 -4 5 1 -3 0 -1 -3 -3 -1 -3 -2 4 0 0 0 0 0 0 0 0 0 54 0 0 0 0 0 0 0 0 0 46 0.62 0.09 52 | 49 H -3 -1 0 -2 -4 -1 -1 -3 10 -5 -4 -2 -3 -2 -3 -2 -3 -4 1 -4 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 1.81 0.18 53 | 50 F -3 -4 -4 -5 -2 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -1 0 0 0 0 1 0 0 0 0 0 1 0 0 97 0 0 0 0 0 2 1.32 0.14 54 | 51 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.14 55 | 52 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -3 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 99 0.78 0.12 56 | 53 M -2 -3 -3 -4 -3 -2 -3 -4 -3 0 1 -3 9 -1 -4 -3 -2 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 1.29 0.18 57 | 54 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.14 58 | 55 N -3 -1 7 0 -4 -1 -1 -1 0 -4 -5 -1 -3 -4 -3 0 -1 -5 -3 -4 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.33 0.15 59 | 56 H -3 -1 0 -2 -4 -1 -1 -3 10 -5 -4 -2 -3 -2 -3 -2 -3 -4 1 -4 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 1.81 0.18 60 | 57 Y -3 -3 -3 -4 -4 -3 -3 -4 1 -2 -2 -3 -2 3 -4 -3 -3 1 8 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 0 0 91 0 1.47 0.15 61 | 58 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -3 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0.79 0.12 62 | 59 P -2 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.43 0.16 63 | 60 N -3 -1 7 0 -4 -1 -1 -1 0 -4 -5 -1 -3 -4 -3 0 -1 -5 -3 -4 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.33 0.15 64 | 61 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 99 0 1 0 0 0 0 0 0 0 0.80 0.11 65 | 62 T -1 -2 -1 -2 -2 -2 -2 -3 -3 -2 -2 -2 -2 -3 -2 1 6 -3 -3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0.99 0.14 66 | 63 I -2 -4 -4 -4 -2 -3 -4 -4 -3 5 1 -3 2 3 -4 -3 -1 -2 0 2 0 0 0 0 0 0 0 0 0 66 0 0 7 19 0 0 0 0 0 8 0.54 0.09 67 | 64 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 68 | 65 P -1 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 97 0 0 0 0 0 2.30 0.15 69 | 66 M -1 -2 -3 -4 -2 -2 -3 -4 -3 1 3 -2 7 -1 -1 -2 -2 -2 -2 0 4 0 0 0 0 0 0 0 0 1 36 0 56 0 3 0 0 0 0 0 0.62 0.11 70 | 67 V -1 -3 -4 -4 -2 -3 -3 -4 -4 3 0 -3 0 0 -3 -3 -1 -4 -2 5 0 0 0 0 0 0 0 0 0 9 0 0 1 2 0 0 0 0 0 88 0.66 0.10 71 | 68 C -1 -5 -4 -5 10 -4 -5 -4 -4 -2 -1 -4 -2 -3 -4 -2 -2 -3 -3 -2 0 0 0 0 93 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 1.95 0.17 72 | 69 A 1 0 -1 0 -3 3 4 -2 -1 -3 -3 3 -2 -4 -2 0 -1 -3 -2 -3 14 0 0 1 0 14 45 0 0 0 0 24 0 0 0 2 0 0 0 0 0.51 0.07 73 | 70 A 5 -2 -2 -3 -1 -2 -2 -1 -2 -2 -2 -2 -2 -3 -2 1 -1 -3 -3 -1 97 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0.76 0.12 74 | 71 I -2 -3 -4 -4 -2 -3 -4 -4 -4 4 4 -3 1 0 -4 -3 -2 -3 -2 1 0 0 0 0 0 0 0 0 0 45 55 0 0 0 0 0 0 0 0 1 0.58 0.08 75 | 72 R -2 7 -1 -2 -4 0 -1 -3 -1 -4 -3 2 -2 -4 -3 -2 -2 -4 -3 -4 0 94 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 1.20 0.13 76 | 73 P -2 -2 1 3 -4 -1 0 -2 -2 -4 -4 1 -3 -4 6 -1 -1 -5 -3 -3 0 0 10 22 0 1 0 0 0 0 0 10 0 0 54 1 1 0 0 0 1.11 0.09 77 | 74 H -3 -2 -1 -3 -1 -1 -2 -3 8 -3 -2 -2 -2 1 -3 -2 -3 1 6 -3 0 0 0 0 1 0 1 0 51 0 3 0 0 1 0 0 0 1 41 0 1.04 0.12 78 | 75 V 0 -3 -3 -3 -1 -2 -3 -3 -3 3 0 -2 0 -1 -3 -1 2 -3 -2 3 6 0 0 0 1 0 0 0 0 31 0 0 0 0 0 1 21 0 0 40 0.34 0.06 79 | 76 Q -1 -1 0 1 -2 2 1 -2 -1 -2 -2 0 -2 -3 -2 1 4 -3 -2 -2 1 0 2 10 0 16 8 0 0 0 0 4 0 0 0 10 49 0 0 0 0.40 0.07 80 | 77 V 4 -2 -3 -3 0 -2 -2 -1 -2 0 -1 -2 -1 -2 -2 0 0 -3 -2 2 68 0 0 0 1 0 0 0 0 3 1 0 0 0 0 0 1 0 0 26 0.42 0.08 81 | 78 P -2 -3 -3 -1 -4 -2 -1 -3 -3 -3 -3 -2 -2 -4 8 -2 -2 -5 -4 -3 0 0 0 2 0 0 1 0 0 0 1 0 2 0 91 0 1 0 0 1 2.06 0.14 82 | 79 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 97 1 0 0 0 0 0 0 0 0 2 0.85 0.12 83 | 80 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.14 84 | 81 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -3 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 99 0.77 0.12 85 | 82 H -3 -1 0 -2 -4 -1 -1 -3 10 -5 -4 -2 -3 -2 -3 -2 -3 -4 1 -4 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 1.81 0.18 86 | 83 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.80 0.11 87 | 84 M -2 -3 -3 -4 -3 -2 -3 -4 -3 0 1 -3 9 -1 -4 -3 -2 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 1.29 0.18 88 | 85 V -1 -3 -4 -4 -1 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 -1 -4 -2 5 1 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 94 0.72 0.11 89 | 86 E -1 3 0 0 -4 1 3 -2 -1 -4 -3 5 -2 -4 -2 0 -1 -4 -3 -3 0 13 1 0 0 1 23 0 0 0 0 58 0 0 0 2 1 0 0 0 0.60 0.08 90 | 87 P -2 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.43 0.16 91 | 88 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 99 0.77 0.12 92 | 89 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 99 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1.42 0.14 93 | 90 E 1 6 -1 0 -3 0 0 -2 -1 -3 -3 1 -2 -4 -2 0 -1 -4 -2 -3 13 67 1 5 0 0 4 1 0 0 0 0 0 0 0 8 1 0 0 0 0.63 0.09 94 | 91 I -2 -3 -4 -4 -2 -3 -4 -4 -4 5 3 -3 2 0 -4 -3 -1 -3 -2 2 0 0 0 0 0 0 0 0 0 58 37 0 5 0 0 0 0 0 0 0 0.56 0.08 95 | 92 V 0 -3 -4 -4 -2 -3 -4 -4 -4 5 1 -3 0 -1 -3 -2 -1 -3 -2 3 7 0 0 0 0 0 0 0 0 65 0 0 0 0 0 0 0 0 0 29 0.55 0.09 96 | 93 P -1 -2 -2 -2 -4 -1 -2 -2 -1 -4 -4 -2 -3 -4 8 -1 -2 -5 -4 -3 4 1 0 1 0 3 0 2 1 0 0 0 0 0 85 1 1 0 0 1 1.86 0.13 97 | 94 Q -1 -2 0 6 -4 1 1 -2 -2 -3 -2 -1 1 -3 -2 0 -1 -4 -3 -3 6 0 1 68 0 7 5 0 0 0 3 0 7 0 0 4 0 0 0 0 0.72 0.09 98 | 95 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 1.41 0.15 99 | 96 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -1 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 97 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0.73 0.12 100 | 97 K -1 2 -1 0 -4 1 1 -2 -1 -4 -3 6 -2 -4 -2 -1 -1 -4 -3 -3 4 3 0 3 0 3 6 0 0 0 0 81 0 0 0 0 0 0 0 0 0.72 0.10 101 | 98 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.80 0.12 102 | 99 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 103 | 100 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.80 0.12 104 | 101 N -1 -1 5 3 -3 -1 0 -1 -1 -3 -4 -1 -3 -3 -2 3 1 -4 -3 -3 0 0 41 16 0 0 0 2 0 0 0 0 0 0 0 33 8 0 0 0 0.55 0.08 105 | 102 V -2 -3 -3 -4 -2 -3 -3 -4 -1 4 1 -3 2 1 -3 -3 -1 -1 4 2 0 0 0 0 0 0 0 0 0 51 8 0 7 1 0 0 0 0 22 9 0.43 0.07 106 | 103 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 99 0 0 0 0 0 0 0 0 0 1 0.87 0.12 107 | 104 T 0 -2 -1 -2 -2 -1 -1 -2 -2 -2 -2 -1 -2 -3 -2 3 6 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 77 0 0 0 0.73 0.11 108 | 105 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 99 0 0 0 0 0 1 1.37 0.14 109 | 106 H -3 -1 0 -2 -4 -1 -1 -3 10 -5 -4 -2 -3 -2 -3 -2 -3 -4 1 -4 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 1.81 0.18 110 | 107 P -1 -3 -3 -3 -4 -2 -2 -3 -3 -3 -4 -2 -3 -5 8 -2 -2 -5 -4 -3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 96 0 0 0 0 1 2.26 0.15 111 | 108 E -2 -1 -1 1 -5 1 6 -3 -1 -4 -4 0 -3 -4 -2 -1 -2 -4 -3 -3 0 0 0 2 0 0 98 0 0 0 0 0 0 0 0 0 0 0 0 0 1.16 0.14 112 | 109 A 5 -2 -2 -2 -1 -2 -2 2 -2 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 88 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 1 0 0 0 0.66 0.10 113 | 110 S 0 -2 0 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 -2 5 1 -4 -3 -2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 94 4 0 0 1 0.79 0.13 114 | 111 R -1 2 0 3 -4 1 5 -3 0 -3 -3 1 -2 -4 -1 -1 -1 -4 -3 -2 1 17 0 16 0 0 56 0 1 0 1 2 0 0 1 0 1 0 0 3 0.58 0.08 115 | 112 H -3 -1 0 -2 -4 -1 -1 -3 10 -5 -4 -2 -3 -2 -3 -2 -3 -4 1 -4 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 1.81 0.18 116 | 113 V -1 -3 -4 -4 -2 -3 -4 -4 -4 5 1 -3 1 -1 -2 -3 -1 -3 -2 4 0 0 0 0 0 0 0 0 0 54 3 0 1 0 1 0 0 0 0 41 0.56 0.08 117 | 114 D -2 -3 1 7 -5 -1 1 -2 0 -4 -5 -2 -4 -4 -2 -1 -2 -5 -4 -4 1 0 0 97 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 1.35 0.13 118 | 115 R -2 7 -1 -3 -5 0 -1 -3 -1 -4 -3 1 -2 -4 -3 -2 -2 -4 -3 -4 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.29 0.14 119 | 116 T 0 -2 0 -1 -1 -1 -1 -2 -2 -2 -2 -1 -2 -3 -2 3 5 -3 -2 -1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 38 60 0 0 0 0.64 0.10 120 | 117 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 1 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 4 95 0 0 0 0 0 0 0 0 1 0.75 0.10 121 | 118 A 1 -1 0 -1 -3 5 0 2 -1 -3 -3 0 -2 -4 -2 2 0 -3 -2 -3 10 0 1 0 0 49 0 16 0 0 0 0 0 0 0 23 1 0 0 0 0.48 0.08 122 | 119 L -2 -3 -4 -4 -2 -2 -4 -4 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 1 0 0 0 0 96 0 3 0 0 0 0 0 0 0 0.75 0.10 123 | 120 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 99 0 0 0 0 0 0 0 0 0 1 0.87 0.12 124 | 121 R -2 6 -1 -2 -4 1 0 -3 0 -4 -3 4 -2 -4 -2 -1 -2 -4 -2 -3 0 58 0 0 0 1 0 0 2 0 0 39 0 0 0 0 0 0 0 0 0.83 0.10 125 | 122 D -2 -2 0 6 -4 0 4 -2 -1 -4 -4 -1 -3 -4 -2 0 -2 -4 -3 -4 2 0 0 61 0 0 33 0 0 0 0 0 0 0 0 4 0 0 0 0 0.91 0.10 126 | 123 H 0 -1 2 -1 2 1 0 -1 7 -3 -2 -1 -1 -2 -2 1 -1 -3 0 -3 7 1 16 0 7 5 3 1 45 0 4 0 1 0 0 10 0 0 1 0 0.50 0.08 127 | 124 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 1 0 0 0 99 0 0 0 0 0 0 0 0 0 0 0 0 1.42 0.12 128 | 125 C -2 -5 -4 -5 10 -4 -5 -4 -4 -2 -2 -4 -2 -4 -4 -2 -2 -4 -4 -2 0 0 0 0 99 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2.17 0.18 129 | 126 K -1 2 -1 -1 -4 4 1 -2 -1 -4 -3 5 -2 -4 -2 -1 -1 -4 -2 -3 0 3 0 0 0 25 2 0 0 0 0 69 0 0 0 0 1 0 0 0 0.73 0.10 130 | 127 A 5 -2 -2 -2 -1 -2 -2 0 -2 -2 -2 -1 -2 -3 -1 1 -1 -3 -3 -1 92 0 0 0 0 0 0 1 0 0 0 0 0 0 1 6 0 0 0 0 0.70 0.11 131 | 128 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 132 | 129 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 1 0 -4 -3 -2 -2 -2 1 0 0 0 0 0 0 0 0 0 2 96 0 0 0 0 0 0 0 0 2 0.75 0.10 133 | 130 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 -1 -4 -2 6 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 98 0.76 0.12 134 | 131 F -3 -4 -4 -5 -3 -4 -4 -4 -2 0 2 -4 0 7 -4 -3 -3 0 2 -1 0 0 0 0 0 0 0 0 0 1 16 0 0 83 0 0 0 0 0 0 1.06 0.12 135 | 132 N -3 -1 7 0 -4 -1 -1 -1 0 -4 -5 -1 -3 -4 -3 0 -1 -5 -3 -4 0 0 99 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1.30 0.15 136 | 133 P -2 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.43 0.16 137 | 134 A 5 -2 -2 -3 -1 -2 -2 1 -2 -2 -2 -2 -2 -3 -2 1 -1 -3 -3 -1 92 0 0 0 0 0 0 7 0 0 0 0 0 0 0 1 1 0 0 0 0.68 0.11 138 | 135 T -1 -2 -1 -2 -2 -2 -2 -3 -3 -2 -2 -2 -2 -3 -2 1 6 -3 -3 -1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 98 0 0 0 0.95 0.14 139 | 136 P -1 -3 -2 -2 -3 -2 -2 -3 -3 -4 -4 -2 -3 -4 8 1 -1 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 1 0 0 0 83 16 0 0 0 0 1.86 0.13 140 | 137 L -2 -3 -4 -4 -2 -3 -4 -4 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 1 1 0 0 0 0 0 0 0 0 1 93 0 1 0 0 0 0 0 0 4 0.71 0.10 141 | 138 H -1 -1 2 1 -3 0 0 -2 6 -3 -3 -1 -2 -2 -2 3 0 -3 1 -3 2 0 11 9 0 1 3 0 38 0 0 0 0 0 0 33 1 0 3 0 0.52 0.08 142 | 139 Y -2 -3 -3 -4 1 -2 -3 -4 3 -1 -1 -3 -2 2 -4 -2 -2 4 7 -1 1 0 0 0 3 0 0 0 9 1 2 0 0 2 0 0 0 5 72 5 1.01 0.12 143 | 140 M -2 -3 -4 -4 -2 -3 -4 -4 -3 1 5 -3 3 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 87 0 12 0 0 0 0 0 0 1 0.70 0.09 144 | 141 D -2 -2 1 7 -4 -1 2 -2 -2 -4 -4 -1 -4 -4 -2 -1 -2 -5 -4 -4 1 0 0 88 0 0 9 0 0 0 1 1 0 0 0 0 0 0 0 0 1.19 0.12 145 | 142 Y -3 -2 0 -3 -4 -1 -2 -3 7 -3 -3 -2 -2 1 -3 -2 -2 2 6 -3 0 0 3 0 0 0 0 0 48 0 0 0 0 1 0 0 0 2 47 0 1.09 0.13 146 | 143 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -2 0 -4 -2 5 1 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 94 0.70 0.11 147 | 144 M -2 -3 -3 -4 -2 -2 -3 -4 -3 1 2 -3 8 -1 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 1 15 0 84 0 0 0 0 0 0 0 1.00 0.15 148 | 145 D -3 -2 1 7 -5 -1 1 -2 -1 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 96 0 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0 1.36 0.13 149 | 146 K -2 3 -1 -1 -4 1 0 -2 -1 -4 -3 6 -2 -4 -2 -1 -1 -4 -3 -3 0 14 0 1 0 0 0 0 0 0 1 83 0 0 0 0 0 0 0 0 0.81 0.11 150 | 147 L -2 -3 -4 -4 -2 -3 -3 -4 -4 3 4 -3 1 0 -3 -3 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 17 59 0 0 0 0 0 0 0 0 24 0.50 0.07 151 | 148 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.14 152 | 149 V -1 -3 -3 -4 -2 -1 -3 -4 -3 2 2 -2 5 -1 -3 -2 -1 -3 -2 3 0 0 0 0 0 2 0 0 0 9 21 0 33 1 0 0 0 0 0 34 0.42 0.07 153 | 150 V -1 -4 -4 -4 -2 -3 -4 -4 -4 5 1 -3 0 -1 -3 -3 -1 -3 -2 4 0 0 0 0 0 0 0 0 0 56 0 0 0 0 0 0 0 0 0 44 0.62 0.09 154 | 151 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 99 0 1 0 0 0 0 0 0 0 0.80 0.11 155 | 152 L -2 -3 -4 -4 -2 -3 -4 -4 -4 3 4 -3 1 0 -4 -3 -2 -3 -2 1 0 0 0 0 0 0 0 0 0 25 73 0 0 0 0 0 0 0 0 1 0.61 0.08 156 | 153 M -2 -3 -3 -4 -3 -2 -3 -4 -3 0 1 -3 9 -1 -4 -3 -2 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 1.29 0.18 157 | 154 S 0 -2 0 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 -2 6 1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.87 0.14 158 | 155 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -3 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0.79 0.12 159 | 156 N -3 -1 7 0 -4 -1 -1 -1 0 -4 -5 -1 -3 -4 -3 0 -1 -5 -3 -4 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.33 0.15 160 | 157 P -2 -3 -3 -3 -4 -2 -2 -3 -3 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.43 0.16 161 | 158 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 162 | 159 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 97 0 0 0 0 3 0 1.37 0.14 163 | 160 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.43 0.12 164 | 161 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 165 | 162 Q -2 0 -1 -1 -4 7 1 -3 0 -4 -3 0 -1 -4 -2 -1 -2 -3 -3 -3 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.28 0.16 166 | 163 A 1 -1 0 -1 -2 0 -1 -1 -2 -3 -3 2 -2 -3 -2 5 1 -4 -2 -2 5 0 0 0 0 2 0 0 0 0 0 14 0 0 0 77 0 0 0 0 0.58 0.10 167 | 164 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 1.41 0.15 168 | 165 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 97 3 0 0 0 0 0 0 0 0 0 0.85 0.12 169 | 166 P -2 -3 -3 -2 -4 -2 -2 -3 -2 -4 -4 -2 -4 -5 8 -2 -2 -5 -4 -3 0 0 0 0 0 0 0 0 1 0 0 0 0 0 99 0 0 0 0 0 2.37 0.15 170 | 167 A 1 -1 0 0 -2 1 2 1 3 -3 -3 0 -2 -3 -2 2 0 -3 -1 -2 18 0 3 0 0 7 24 12 12 0 0 0 0 0 0 21 2 0 1 0 0.29 0.05 171 | 168 T 2 -2 -1 -2 -1 -1 -2 -2 -2 -1 -2 -1 -1 -3 -2 1 5 -3 -2 0 28 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2 66 0 0 2 0.55 0.10 172 | 169 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 2 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 2 96 0 2 0 0 0 0 0 0 0 0.76 0.10 173 | 170 A -1 -1 3 4 -3 0 2 -1 -1 -3 -3 0 -3 -4 -1 0 0 -4 -3 -2 6 1 20 41 0 1 11 2 1 0 0 6 0 0 2 0 4 0 0 4 0.46 0.05 174 | 171 K -2 1 -1 -2 -4 1 0 -2 -2 -4 -3 6 -2 -4 -2 -1 -2 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 1.00 0.14 175 | 172 L -1 -3 -4 -4 -2 -3 -3 -4 -4 2 4 -3 1 0 -3 -3 -1 -2 -2 1 4 0 0 0 0 0 0 0 0 16 77 0 0 0 0 0 0 0 0 3 0.56 0.08 176 | 173 R 0 6 -1 -2 -3 1 0 -3 -1 -4 -3 2 -2 -4 -3 -1 -1 -4 -2 -3 10 76 0 0 0 2 2 0 0 0 0 9 0 0 0 0 1 0 0 0 0.83 0.10 177 | 174 D 1 0 -1 1 -3 4 4 -2 -1 -2 -2 0 -1 -3 -2 0 -1 -3 -2 -2 15 0 0 4 0 37 36 0 0 1 2 0 1 0 0 1 2 0 0 1 0.49 0.07 178 | 175 A 3 -3 -3 -3 -1 -2 -2 -2 -3 1 0 -2 -1 -2 -2 0 0 -3 -2 3 49 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 0 0 46 0.38 0.08 179 | 176 R -2 7 -1 -3 -5 0 -1 -3 -1 -4 -3 2 -2 -4 -3 -2 -2 -4 -3 -4 0 99 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1.27 0.14 180 | 177 A 2 2 -1 -1 -2 3 1 -1 -1 -3 -2 3 -2 -3 -2 0 -1 -3 -2 -2 32 15 0 0 0 18 8 0 1 0 0 22 0 0 0 2 1 0 0 0 0.34 0.05 181 | 178 R -2 6 -1 -3 -3 0 -1 -3 -1 -1 0 2 1 -2 -3 -2 -2 -3 -2 -2 0 67 0 0 0 0 0 0 0 5 13 9 6 0 0 0 0 0 0 0 0.62 0.09 182 | 179 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 2 -4 1 -1 -4 -3 -1 -3 -2 2 1 0 0 0 0 0 0 0 0 88 11 0 0 0 0 0 0 0 0 1 0.73 0.11 183 | 180 D -2 -2 1 7 -4 -1 1 -2 -2 -4 -4 -1 -4 -4 -2 -1 -2 -5 -4 -4 0 0 2 92 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1.24 0.12 184 | 181 R 2 1 0 1 -1 0 2 -1 -1 -2 -1 0 -1 -2 -1 0 0 -2 -1 -1 30 9 2 10 1 2 23 2 1 1 4 3 2 1 2 2 4 0 1 2 0.17 0.02 185 | 182 W -1 -1 -1 -1 -1 -1 -1 -1 2 -1 -1 -1 -1 1 -1 -1 -1 6 5 -1 4 3 2 3 1 2 3 4 5 3 5 3 1 2 3 4 3 12 33 4 0.30 0.02 186 | 183 R 0 1 0 0 -1 1 1 -1 -1 -1 -1 0 0 -1 0 0 2 -1 0 0 7 11 3 3 1 4 10 4 1 3 5 6 3 2 3 4 20 1 3 6 0.06 0.01 187 | 184 A 2 0 0 1 -1 1 1 0 -1 -1 -1 0 -1 -1 0 0 0 -1 -1 -1 26 4 3 7 1 7 14 5 1 3 4 3 1 2 3 4 5 1 2 3 0.10 0.01 188 | 185 A 2 2 0 -1 -2 2 1 -1 -1 -2 -2 1 -1 -2 -1 0 0 -2 -1 -1 33 18 3 2 0 11 7 2 1 1 2 9 1 1 1 4 1 0 1 2 0.19 0.03 189 | 186 G 0 -1 0 -1 -2 -1 -1 1 1 -3 -3 -1 -2 -3 -2 4 3 -3 -2 -2 0 0 1 0 0 0 0 13 4 0 0 0 0 0 0 61 20 0 0 0 0.48 0.08 190 | 187 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 1 0 0 0 99 0 0 0 0 0 0 0 0 0 0 0 0 1.40 0.12 191 | 188 Q -2 5 -1 -2 -3 2 -1 -1 1 -3 -1 1 -1 1 -3 -1 -2 -2 3 -2 0 53 1 0 0 12 0 4 3 0 6 1 0 7 0 0 0 0 13 0 0.45 0.07 192 | 189 P -1 0 2 4 -4 1 3 -2 2 -4 -3 0 -3 -4 2 0 -1 -4 -2 -3 3 7 8 41 0 2 19 0 6 0 0 2 0 0 9 1 2 0 0 0 0.52 0.06 193 | 190 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 98 0 0 0 0 0 0 0 0 0 2 0.86 0.12 194 | 191 L -1 5 -2 -2 -3 0 -1 -3 2 -2 0 1 1 -2 -3 -2 -2 5 -1 -2 6 51 0 0 0 0 0 0 9 0 15 1 5 0 0 0 0 12 0 2 0.47 0.08 195 | 192 L -2 -3 -4 -5 -2 -3 -4 -5 -4 1 5 -3 1 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 3 96 0 0 0 0 0 0 0 0 1 0.76 0.10 196 | 193 E -2 -1 -1 1 -5 2 6 -3 -1 -4 -4 0 -3 -4 -2 -1 -2 -4 -3 -3 0 0 0 0 0 6 94 0 0 0 0 0 0 0 0 0 0 0 0 0 1.11 0.13 197 | 194 V -1 -3 -4 -4 -2 -3 -3 -4 -4 4 1 -3 0 -1 -3 -3 -1 -4 -2 5 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 0 0 68 0.62 0.09 198 | 195 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.14 199 | 196 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 200 | 197 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 201 | 198 V -1 -3 -4 -4 -2 -3 -3 -4 -4 3 0 -3 0 -1 -3 -3 -1 -4 -2 5 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 86 0.68 0.10 202 | 199 K -2 1 0 -1 -4 1 0 -2 -2 -4 -3 6 -2 -4 -2 -1 -1 -4 -3 -3 0 0 3 0 0 0 0 0 0 0 0 95 0 0 0 0 1 0 0 0 0.91 0.13 203 | 200 V 1 -3 -3 -3 -1 -2 -2 -3 -3 2 0 -2 0 -2 0 -1 1 -3 -2 4 13 0 0 0 0 0 0 0 0 11 1 0 0 0 3 0 9 0 0 61 0.34 0.07 204 | 201 D -2 -2 2 6 -4 -1 2 -1 -2 -4 -4 -1 -4 -4 -2 0 -2 -5 -4 -4 1 0 7 79 0 0 8 2 0 0 0 0 0 0 0 3 0 0 0 0 1.02 0.10 205 | 202 N -3 -1 7 0 -4 -1 -1 -1 0 -4 -5 -1 -3 -4 -3 0 -1 -5 -3 -4 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.33 0.15 206 | 203 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -2 -4 -2 2 0 0 0 0 0 0 0 0 0 99 1 0 0 0 0 0 0 0 0 0 0.87 0.12 207 | 204 A 4 2 -2 -2 -2 -1 -1 2 -2 -2 -2 -1 -2 -3 -2 0 -1 -3 -3 -1 71 15 0 0 0 0 0 13 0 0 0 1 0 0 0 0 0 0 0 0 0.48 0.08 208 | 205 E 1 -1 -1 1 -3 2 5 -2 -1 -4 -3 0 -2 -4 -2 0 -1 -4 -3 -3 17 0 0 5 0 9 67 0 0 0 0 1 0 0 0 0 0 0 0 0 0.68 0.09 209 | 206 I -1 -4 -4 -4 -1 -3 -4 -4 -4 5 1 -3 1 -1 -3 -3 -1 -3 -2 3 6 0 0 0 0 0 0 0 0 82 1 0 1 0 0 0 0 0 0 10 0.63 0.10 210 | 207 R 5 1 -2 -2 -1 -1 -1 -1 -1 -2 -2 0 -2 -3 -2 0 -1 -3 -2 -1 83 9 0 0 0 0 0 0 1 0 0 4 0 0 0 0 0 0 1 1 0.54 0.10 211 | 208 A 4 2 -2 -1 -2 0 1 -1 -2 -2 -2 0 -2 -3 -2 0 -1 -3 -2 -1 66 14 0 1 0 2 12 1 0 0 0 4 0 0 0 0 0 0 0 0 0.41 0.08 212 | 209 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0.79 0.12 213 | 210 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 214 | 211 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 0 96 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0.73 0.12 215 | 212 D -3 -3 1 7 -5 -1 1 -2 -2 -4 -5 -2 -4 -5 -2 -1 -2 -5 -4 -4 0 0 1 99 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.43 0.14 216 | 213 T -1 -2 -1 -2 -2 -1 -2 -3 -2 -1 0 -2 5 -2 -2 0 5 -3 -2 0 2 0 0 0 0 0 0 0 0 0 0 0 34 0 0 1 62 0 0 0 0.60 0.12 217 | 214 F -3 -4 -4 -5 -1 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 2 -2 0 0 0 0 1 0 0 0 0 0 1 0 0 98 0 0 0 0 0 0 1.35 0.14 218 | 215 V -1 -3 -4 -4 -2 -3 -3 -4 -4 2 0 -3 0 -2 -3 -3 -1 -4 -2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0.79 0.12 219 | 216 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.80 0.12 220 | 217 G -1 -3 -1 -2 -3 -3 -3 7 -3 -5 -5 -2 -4 -4 -3 -1 -2 -3 -4 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.44 0.12 221 | 218 S 0 -2 0 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 -2 6 1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.87 0.14 222 | 219 A 5 -2 -2 -3 -1 -2 -2 -1 -3 -2 -2 -2 -2 -3 -2 0 -1 -3 -3 -1 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.80 0.12 223 | 220 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 0 -1 -4 -3 -1 -4 -2 3 0 0 0 0 0 0 0 0 0 88 0 0 0 0 0 0 0 0 0 12 0.76 0.11 224 | 221 F -3 -4 -4 -5 -3 -4 -4 -4 -2 -1 0 -4 -1 8 -5 -3 -3 0 3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 93 0 0 0 0 7 0 1.31 0.14 225 | 222 G -1 -2 3 0 -3 -2 -2 5 -2 -4 -4 -2 -3 -4 -3 1 -1 -4 -3 -4 0 0 22 5 0 0 0 65 0 0 0 0 0 0 0 9 0 0 0 0 0.82 0.08 226 | 223 K 1 1 -1 -1 -3 5 1 -2 1 -3 -3 3 -1 -4 -2 0 0 -3 -2 -2 13 0 0 0 0 42 1 0 4 0 0 31 0 0 0 1 8 0 0 0 0.47 0.08 227 | 224 P -1 -2 -2 -1 -3 -2 -1 -1 1 -4 -4 -1 -3 -4 7 -1 -2 -4 -3 -3 4 0 0 4 0 0 0 4 5 0 0 3 1 0 76 2 0 0 0 0 1.58 0.11 228 | 225 D -3 0 1 7 -3 -1 1 -2 -2 -4 -4 -1 -4 -4 -2 -1 -2 -5 -4 -4 0 5 2 89 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1.18 0.12 229 | 226 Y -3 -3 -3 -4 -4 -2 -3 -4 1 -2 -2 -3 -2 2 -4 -3 -3 1 9 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 99 0 1.60 0.16 230 | 227 A 1 3 0 1 -3 1 0 -2 -1 -3 -3 4 -2 -4 -1 0 -1 -4 -2 -3 15 13 1 7 0 6 1 1 0 0 0 55 0 0 1 0 1 0 0 0 0.45 0.07 231 | 228 Q 3 -1 -1 -1 -2 1 0 1 -1 -2 -2 1 -1 -3 -1 1 1 -3 -2 -1 49 1 0 0 0 9 3 7 1 0 0 9 0 0 0 8 11 0 0 2 0.28 0.05 232 | 229 V -1 -3 -3 -3 -2 -3 -3 -4 -4 3 0 -3 0 -2 -3 -2 1 -4 -2 5 1 0 0 0 0 0 1 0 0 11 1 0 0 0 0 0 12 0 0 75 0.51 0.09 233 | 230 I -2 -4 -4 -4 -2 -4 -4 -5 -4 6 1 -4 1 -1 -4 -3 -1 -3 -2 2 0 0 0 0 0 0 0 0 0 93 2 0 1 0 0 0 0 0 0 4 0.79 0.11 234 | 231 G 1 -1 1 5 -3 1 1 0 -1 -3 -4 0 -3 -4 -2 0 -1 -4 -3 -3 16 3 4 55 0 5 5 5 0 0 0 4 0 0 0 1 2 0 0 0 0.55 0.07 235 | 232 Q 3 0 -1 1 -2 3 2 -1 -1 -3 -2 1 -2 -3 -2 0 -1 -3 -2 -2 40 2 1 7 0 18 18 1 1 0 1 8 0 0 0 3 1 0 0 0 0.31 0.06 236 | 233 L -2 -3 -3 -4 -2 -2 -3 -4 -3 0 2 -3 8 0 -4 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 0 13 0 86 1 0 0 0 0 0 0 1.04 0.16 237 | 234 R -2 7 -1 -3 -3 0 -1 -3 0 -4 -3 2 -2 -4 -3 -2 -2 -4 -3 -4 0 97 0 0 1 0 0 0 1 0 0 2 0 0 0 0 0 0 0 0 1.24 0.14 238 | 235 A 3 0 0 0 -1 1 1 0 -1 -2 -2 0 -2 -3 -2 1 0 -3 -2 -1 48 4 3 3 1 9 9 4 0 0 1 1 0 0 0 11 4 0 0 1 0.26 0.05 239 | 236 E 0 -1 -1 0 -4 3 5 -2 -1 -4 -3 0 -2 -4 -2 -1 -1 -4 -3 -3 8 0 1 0 0 19 71 0 0 0 0 1 0 0 0 0 0 0 0 0 0.81 0.11 240 | 237 I -2 -3 -4 -4 -2 -3 -4 -4 -4 2 5 -3 2 0 -4 -3 -2 -2 -2 1 1 0 0 0 0 0 0 0 0 16 80 0 1 0 0 0 0 0 0 2 0.62 0.09 241 | 238 A 5 -2 -2 -2 -1 -1 0 0 -2 -2 -2 -1 -2 -3 -1 1 -1 -3 -3 -1 86 0 0 0 0 0 6 1 0 0 2 0 0 0 0 4 0 0 0 0 0.60 0.11 242 | 239 R -1 2 0 -1 -3 2 0 -1 -1 -2 -2 5 -1 -3 -2 0 0 -3 -2 -2 4 8 2 0 0 9 0 2 1 3 3 61 1 0 0 3 3 0 0 0 0.43 0.07 243 | 240 G 2 -2 -2 -3 -1 -2 -2 1 -3 1 -1 -2 -1 -2 -2 0 0 -3 -2 3 33 0 0 0 0 0 0 9 0 1 0 0 0 0 0 7 1 0 0 49 0.27 0.06 244 | 241 E -1 1 1 2 -3 2 3 0 0 -3 -3 2 -2 -3 -2 0 0 -3 -2 -2 1 4 8 8 0 9 30 7 1 0 0 21 0 0 0 2 8 0 0 2 0.32 0.03 245 | 242 T 2 0 -1 -1 0 1 0 -1 -1 -2 -2 0 -1 -3 -1 2 2 -3 -2 -1 33 4 0 2 2 8 1 1 1 0 0 3 0 0 1 22 21 0 0 0 0.25 0.03 246 | 243 I -1 -1 -1 -2 -2 1 0 -1 -2 1 2 -1 1 -1 -2 0 1 -2 -2 1 0 0 0 0 0 12 3 6 0 10 33 3 0 0 0 6 18 0 0 9 0.10 0.01 247 | 244 A 3 -1 0 -1 -1 -1 -1 0 -1 -2 -2 -1 -1 -3 -1 2 1 -3 -2 -1 60 0 5 0 0 0 0 0 0 0 0 0 0 0 0 28 7 0 0 0 0.35 0.02 248 | 245 V -1 -2 -2 -3 -1 -2 -2 -3 -3 2 2 -2 1 -1 -2 -1 1 -3 -1 3 0 0 0 0 0 0 0 0 0 14 25 0 0 0 0 0 19 0 0 42 0.24 0.00 249 | 250 | K Lambda 251 | Standard Ungapped 0.1382 0.3231 252 | Standard Gapped 0.0410 0.2670 253 | PSI Ungapped 0.1679 0.3195 254 | PSI Gapped 0.0514 0.2670 255 | -------------------------------------------------------------------------------- /src/pssmpro/data/pssm_files/example_1.pssm: -------------------------------------------------------------------------------- 1 | 2 | Last position-specific scoring matrix computed, weighted observed percentages rounded down, information per position, and relative weight of gapless real matches to pseudocounts 3 | A R N D C Q E G H I L K M F P S T W Y V A R N D C Q E G H I L K M F P S T W Y V 4 | 1 M -1 -1 -2 -3 -2 0 -2 -3 -2 1 2 -1 6 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0.33 0.00 5 | 2 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -1 -3 -1 0 -1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.51 0.00 6 | 3 Q -1 1 0 0 -3 6 2 -2 0 -3 -2 1 0 -3 -1 0 -1 -2 -2 -2 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.64 0.00 7 | 4 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -1 -3 -1 0 -1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.51 0.00 8 | 5 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.38 0.00 9 | 6 D -2 -2 1 6 -4 0 2 -1 -1 -3 -4 -1 -3 -4 -2 0 -1 -4 -3 -3 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.92 0.00 10 | 7 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0.85 0.00 11 | 8 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.38 0.00 12 | 9 A 4 -2 -2 -2 0 -1 -1 0 -2 -1 -2 -1 -1 -2 -1 1 0 -3 -2 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.40 0.00 13 | 10 R -2 6 0 -2 -4 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1 -3 -2 -3 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.74 0.00 14 | 11 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0.85 0.00 15 | 12 F -2 -3 -3 -4 -2 -3 -3 -4 -2 1 3 -3 1 5 -3 -3 -2 0 2 0 0 0 0 0 0 0 0 0 0 0 50 0 0 50 0 0 0 0 0 0 0.43 0.00 16 | 13 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -1 -3 -1 0 -1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.51 0.00 17 | 14 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.45 0.00 18 | 15 M -1 1 -1 -2 -2 1 0 -2 -1 0 1 3 4 -1 -2 -1 -1 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 50 50 0 0 0 0 0 0 0 0.20 0.00 19 | 16 S 1 -1 1 0 -1 0 0 0 -1 -2 -3 0 -2 -3 -1 4 1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.45 0.00 20 | 17 P -1 -2 -2 -2 -3 -1 -1 -2 -2 -3 -3 -1 -3 -4 8 -1 -1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.03 0.00 21 | 18 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -3 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.41 0.01 22 | 19 I -1 1 -1 -2 -2 0 -1 -3 -2 3 0 3 0 -1 -2 -1 -1 -3 -2 1 0 0 0 0 0 0 0 0 0 51 0 49 0 0 0 0 0 0 0 0 0.16 0.00 23 | 20 N 0 -1 4 1 -2 0 0 0 0 -3 -3 0 -2 -3 -1 3 1 -3 -2 -2 0 0 51 0 0 0 0 0 0 0 0 0 0 0 0 49 0 0 0 0 0.46 0.01 24 | 21 R -1 4 0 -1 -3 1 1 -2 -1 -3 -3 4 -1 -3 -1 0 -1 -3 -2 -3 0 25 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0.52 0.01 25 | 22 E -1 0 0 2 -4 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.75 0.01 26 | 23 E -1 0 0 2 -4 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.75 0.01 27 | 24 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -3 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.41 0.01 28 | 25 N -1 1 4 3 -3 0 1 -1 0 -3 -3 3 -2 -3 -2 0 -1 -4 -2 -3 0 0 42 21 0 0 0 0 0 0 0 37 0 0 0 0 0 0 0 0 0.45 0.01 29 | 26 N -2 -1 4 5 -3 0 1 -1 -1 -3 -4 -1 -3 -4 -2 0 -1 -4 -3 -3 0 0 34 66 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.75 0.01 30 | 27 I -2 -3 -4 -4 -1 -3 -3 -4 -3 3 4 -3 2 0 -3 -3 -1 -2 -1 2 0 0 0 0 0 0 0 0 0 34 66 0 0 0 0 0 0 0 0 0 0.40 0.01 31 | 28 V 0 -3 -3 -3 -1 -2 -3 -3 -3 3 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0.39 0.02 32 | 29 K -1 2 -1 -1 -3 1 0 -2 -1 0 -1 4 -1 -3 -1 -1 -1 -3 -2 -1 0 0 0 0 0 0 0 0 0 17 0 83 0 0 0 0 0 0 0 0 0.35 0.01 33 | 30 A 2 -1 3 2 -2 0 1 0 -1 -2 -2 0 -2 -3 -1 1 0 -3 -2 -1 47 0 27 12 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0.29 0.01 34 | 31 Q 0 0 0 -1 -2 3 1 -1 -1 -3 -3 0 -1 -3 3 3 1 -3 -2 -2 0 0 0 0 0 34 0 0 0 0 0 0 0 0 13 53 0 0 0 0 0.42 0.01 35 | 32 D 0 -1 1 3 -2 -1 0 -1 -1 -2 -2 -1 -2 1 -1 3 0 -2 -1 -2 0 0 0 34 0 0 0 0 0 0 0 0 0 14 0 52 0 0 0 0 0.33 0.01 36 | 33 E 1 0 -1 1 -3 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1 -3 -2 -2 17 0 0 0 0 0 83 0 0 0 0 0 0 0 0 0 0 0 0 0 0.59 0.01 37 | 34 L -2 -3 -3 -4 -2 -3 -3 -4 -2 0 2 -3 1 5 -4 -3 -2 0 2 0 0 0 0 0 0 0 0 0 0 0 34 0 0 66 0 0 0 0 0 0 0.53 0.01 38 | 35 E -1 1 0 1 -4 2 4 -2 0 -3 -3 3 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 56 0 0 0 0 44 0 0 0 0 0 0 0 0 0.54 0.01 39 | 36 I -1 -1 -1 1 -3 1 4 -2 -1 0 -1 0 -1 -2 -1 0 1 -3 -2 -1 0 0 0 0 0 0 66 0 0 17 0 0 0 0 0 0 17 0 0 0 0.37 0.01 40 | 37 T -1 -3 -3 -3 -1 -3 -3 -4 -3 4 1 -2 1 -1 -3 -1 1 -3 -2 2 0 0 0 0 0 0 0 0 0 83 0 0 0 0 0 0 17 0 0 0 0.32 0.01 41 | 38 G 0 -3 -1 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -3 -3 -3 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.09 0.02 42 | 39 A 1 3 -1 -1 -3 1 0 -1 -1 -3 -2 4 -1 -3 -1 0 -1 -3 -2 -2 17 27 0 0 0 0 0 0 0 0 0 56 0 0 0 0 0 0 0 0 0.41 0.01 43 | 40 P -1 -2 -2 -2 -3 -1 -1 -2 -2 -3 -3 -1 -3 -4 8 -1 -1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.09 0.02 44 | 41 E -1 -2 -2 -1 -2 0 2 -3 -2 3 0 -1 0 -1 -2 -1 1 -3 -2 1 0 0 0 0 0 0 34 0 0 52 0 0 0 0 0 0 13 0 0 0 0.18 0.01 45 | 42 H -2 0 0 -1 -3 0 0 -2 8 -4 -3 -1 -2 -1 -2 -1 -2 -3 2 -3 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0.99 0.03 46 | 43 G 0 -3 -1 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -3 -3 -3 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.09 0.02 47 | 44 S 0 -1 0 -1 -1 -1 -1 -1 -2 -1 -2 -1 -1 -2 -1 3 4 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 34 66 0 0 0 0.42 0.01 48 | 45 H -2 -2 -2 -3 -2 -1 -2 -3 5 1 3 -2 1 0 -3 -2 -2 -2 0 0 0 0 0 0 0 0 0 0 34 0 66 0 0 0 0 0 0 0 0 0 0.33 0.01 49 | 46 K 1 1 0 -1 -2 0 0 -1 -1 -3 -3 3 -2 -3 -1 3 1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 66 0 0 0 0 0.37 0.01 50 | 47 L 0 -1 0 -1 -1 -1 -1 -1 -2 0 2 -1 0 -1 -2 3 1 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 66 0 0 0 0 0.22 0.01 51 | 48 S 2 -1 0 -1 -1 -1 -1 -1 -1 -1 -2 -1 -1 -2 -1 3 1 -3 -2 1 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 69 0 0 0 17 0.29 0.01 52 | 49 I -2 -2 -3 -3 -2 -2 -2 -3 1 1 0 -2 0 2 -3 -2 -1 1 6 1 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 66 17 0.51 0.01 53 | 50 V 0 -3 -3 -3 -1 -2 -3 -3 -3 3 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0.39 0.02 54 | 51 K -1 3 0 -1 -3 3 1 -2 0 -3 -3 4 -1 -3 -1 0 -1 -3 -2 -2 0 13 0 0 0 27 0 0 0 0 0 60 0 0 0 0 0 0 0 0 0.50 0.01 55 | 52 E -2 -1 1 2 -3 1 2 -2 7 -4 -3 -1 -2 -2 -2 -1 -2 -3 1 -3 0 0 0 17 0 0 17 0 66 0 0 0 0 0 0 0 0 0 0 0 0.65 0.02 56 | 53 L -1 0 -1 -2 -2 0 -1 -3 -2 1 2 2 1 -1 -2 -1 1 -3 -2 0 0 0 0 0 0 0 0 0 0 13 34 39 0 0 0 0 14 0 0 0 0.14 0.01 57 | 54 E -1 -1 2 2 -3 1 3 1 -1 -3 -3 0 -2 -3 -2 0 1 -3 -2 -2 0 0 13 12 0 0 43 14 0 0 0 0 0 0 0 0 17 0 0 0 0.37 0.01 58 | 55 T 0 0 0 -1 -1 0 -1 -2 -2 -1 -2 1 -1 -2 -1 1 5 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 17 0 0 0 0 83 0 0 0 0.41 0.02 59 | 56 G 0 -2 0 -1 -3 -1 1 5 -2 -4 -4 -1 -3 -3 -2 0 -2 -3 -3 -3 0 0 0 0 0 0 17 83 0 0 0 0 0 0 0 0 0 0 0 0 0.82 0.01 60 | 57 F -1 0 3 -1 -2 1 -1 -2 -1 0 0 1 2 2 -2 -1 -1 -2 0 0 0 0 27 0 0 13 0 0 0 0 0 12 13 17 0 0 0 0 0 17 0.11 0.01 61 | 58 E -1 -2 -2 -1 -2 0 2 -3 -2 3 1 -1 2 -1 -2 -1 -1 -3 -2 1 0 0 0 0 0 0 34 0 0 53 0 0 13 0 0 0 0 0 0 0 0.19 0.01 62 | 59 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -2 -1 -2 -1 3 -3 -2 -2 2 7 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 1.04 0.04 63 | 60 V -1 -3 -3 -4 -1 -2 -3 -4 -3 2 2 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 75 0.36 0.02 64 | 61 Q -1 1 -1 -1 -3 3 1 -2 -1 0 -1 3 -1 -3 -2 -1 -1 -3 -2 1 0 0 0 0 0 25 0 0 0 0 0 50 0 0 0 0 0 0 0 25 0.28 0.02 65 | 62 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.62 0.03 66 | 63 Q 0 -1 0 -1 -3 2 -1 5 -1 -4 -4 -1 -2 -3 -2 0 -2 -3 -3 -3 0 0 0 0 0 25 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0.76 0.02 67 | 64 T 4 -2 -1 -2 -1 -1 -1 0 -2 -1 -2 -1 -1 -2 -1 1 2 -3 -2 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0.37 0.02 68 | 65 K -1 2 0 -1 -3 3 1 -2 6 -3 -3 2 -1 -2 -2 -1 -1 -3 0 -3 0 13 0 0 0 25 0 0 50 0 0 13 0 0 0 0 0 0 0 0 0.55 0.03 69 | 66 N 1 -1 3 0 -1 0 0 0 -1 -3 -3 0 -2 -3 -1 4 1 -3 -2 -2 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0.46 0.03 70 | 67 Q -1 5 0 -1 -4 3 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1 -3 -2 -3 0 75 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.69 0.03 71 | 68 T -1 1 0 1 -3 1 4 -2 -1 -3 -2 1 -2 -3 -1 1 2 -3 -2 -2 0 10 0 0 0 0 55 0 0 0 0 0 0 0 0 10 25 0 0 0 0.42 0.02 72 | 69 E -1 -1 1 5 -4 3 3 -2 -1 -3 -3 0 -2 -4 -2 0 -1 -3 -3 -3 0 0 0 50 0 25 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0.64 0.02 73 | 70 T -1 -2 -2 -3 -1 -2 -3 -3 -3 2 3 -2 1 0 -2 -1 2 -2 -1 1 0 0 0 0 0 0 0 0 0 29 45 0 0 0 0 0 25 0 0 0 0.26 0.01 74 | 71 E -1 -2 -2 -1 -2 -1 2 -3 -2 3 0 -1 0 -1 -2 -1 -1 -3 -2 3 0 0 0 0 0 0 25 0 0 25 0 0 0 0 0 0 0 0 0 50 0.22 0.02 75 | 72 K -1 4 0 -1 -3 1 0 -2 -1 -3 -3 5 -2 -3 -1 0 -1 -3 -2 -3 0 25 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0.57 0.03 76 | 73 E -1 0 0 1 -4 2 6 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.83 0.04 77 | 74 F -2 -3 -3 -4 -2 -3 -3 -4 -2 1 3 -3 1 5 -4 -3 -2 0 2 0 0 0 0 0 0 0 0 0 0 0 50 0 0 50 0 0 0 0 0 0 0.48 0.02 78 | 75 M -1 -2 -3 -3 -2 -1 -2 -3 -2 1 2 -2 6 0 -3 -2 -1 -2 -1 2 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 25 0.40 0.04 79 | 76 M -1 -3 -3 -3 -1 -2 -3 -4 -3 4 2 -2 3 0 -3 -2 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 55 0 0 25 0 0 0 0 0 0 20 0.35 0.02 80 | 77 A 2 -1 0 -1 -1 0 0 0 -1 -2 -2 0 -2 -3 -1 4 1 -3 -2 -1 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0.43 0.03 81 | 78 S -1 -1 4 0 -2 0 -1 1 0 -3 -3 -1 -2 -3 -2 1 2 -3 -2 -2 0 0 50 0 0 0 0 13 0 0 0 0 0 0 0 13 25 0 0 0 0.42 0.02 82 | 79 F 4 -2 -2 -2 -1 -1 -2 -1 -2 -1 -1 -1 -1 3 -2 0 -1 -1 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0.31 0.02 83 | 80 L -2 -2 -4 -4 -1 -2 -3 -4 -3 1 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.52 0.03 84 | 81 N -2 -1 5 0 -3 0 0 -1 6 -4 -3 -1 -2 -2 -2 0 -1 -3 0 -3 0 0 50 0 0 0 0 0 50 0 0 0 0 0 0 0 0 0 0 0 0.69 0.03 85 | 82 K -1 1 -1 0 -3 1 3 -2 -1 -1 1 3 0 -2 -2 -1 -1 -3 -2 -1 0 0 0 0 0 0 29 0 0 0 25 45 0 0 0 0 0 0 0 0 0.26 0.02 86 | 83 V -1 -3 -3 -3 -1 -3 -3 -4 -4 4 1 -3 1 0 -3 -2 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 25 0.42 0.02 87 | 84 N -2 4 3 3 -4 0 0 -2 0 -3 -3 1 -2 -3 -2 0 -1 -4 -2 -3 0 50 25 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.51 0.02 88 | 85 P 0 0 0 0 -3 1 3 -2 -1 -3 -3 2 -2 -3 4 2 0 -3 -2 -2 0 0 0 0 0 0 29 0 0 0 0 20 0 0 25 25 0 0 0 0 0.52 0.02 89 | 86 N -1 -1 3 3 -4 1 4 -2 0 -4 -3 0 -2 -4 -2 0 -1 -4 -2 -3 0 0 25 20 0 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0 0.59 0.02 90 | 87 H -1 1 0 -1 -3 5 1 -2 5 -3 -3 1 -1 -3 -2 0 -1 -2 0 -3 0 0 0 0 0 75 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0.65 0.03 91 | 88 P -1 -2 -2 -2 -3 -2 -1 -2 -3 -3 -3 -1 -3 -4 8 -1 -1 -4 -3 -3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 2.13 0.04 92 | 89 K -1 1 0 1 -4 2 4 -2 0 -3 -3 3 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 62 0 0 0 0 38 0 0 0 0 0 0 0 0 0.58 0.02 93 | 90 C 0 -3 -2 -3 9 -2 -3 -2 -3 -2 -2 -2 -2 -3 -2 2 0 -3 -3 -1 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0.95 0.04 94 | 91 K 1 0 -2 -2 -2 -1 -1 -2 -2 0 2 2 1 -1 -2 -1 -1 -2 -2 0 25 0 0 0 0 0 0 0 0 0 50 25 0 0 0 0 0 0 0 0 0.15 0.01 95 | 92 L -2 -3 -4 -4 -1 -3 -3 -4 -3 3 3 -3 2 0 -3 -3 -1 -2 -1 2 0 0 0 0 0 0 0 0 0 50 50 0 0 0 0 0 0 0 0 0 0.40 0.02 96 | 93 V -1 -2 -3 -4 -1 -2 -3 -3 -3 2 3 -2 4 0 -3 -2 -1 -2 -1 2 0 0 0 0 0 0 0 0 0 0 45 0 30 0 0 0 0 0 0 25 0.34 0.02 97 | 94 E -1 0 0 3 -4 4 3 -2 0 -3 -3 1 -1 -4 -1 0 -1 -3 -2 -3 0 0 0 25 0 50 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0.02 98 | 95 T 0 -1 0 -1 -1 -1 -1 -1 -2 -1 -2 -1 -1 -2 -1 2 5 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 75 0 0 0 0.47 0.03 99 | 96 N -2 0 5 3 -3 0 0 -1 0 -3 -4 1 -3 -3 -2 0 0 -4 -3 -3 0 0 65 25 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0.63 0.02 100 | 97 N 0 -1 4 0 -2 -1 -1 4 -1 -3 -4 -1 -2 -3 -2 2 0 -3 -3 -3 0 0 35 0 0 0 0 40 0 0 0 0 0 0 0 25 0 0 0 0 0.51 0.02 101 | 98 G 1 0 -2 -2 -2 -2 -2 2 -2 -1 -1 -1 -1 4 -2 -1 -1 -1 1 -1 25 10 0 0 0 0 0 25 0 0 0 0 0 40 0 0 0 0 0 0 0.25 0.01 102 | 99 S -1 0 1 -1 -3 5 1 -2 0 -3 -2 1 -1 1 -2 1 -1 -2 -1 -2 0 0 10 0 0 65 0 0 0 0 0 0 0 13 0 13 0 0 0 0 0.41 0.03 103 | 100 V -2 -2 -3 -3 -2 -2 -2 -3 1 0 -1 -2 -1 2 -3 -2 -1 1 7 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 25 0.65 0.03 104 | 101 S -1 3 2 -1 -3 0 0 -2 6 -3 -3 0 -2 -2 -2 1 -1 -3 0 -3 0 25 13 0 0 0 0 0 50 0 0 0 0 0 0 13 0 0 0 0 0.51 0.02 105 | 102 I 0 -2 -1 -2 -1 -1 -2 -2 -2 2 0 -1 0 -2 -2 1 4 -3 -2 1 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 75 0 0 0 0.36 0.03 106 | 103 L -2 -2 -3 -4 -2 -2 -3 -4 -3 1 4 -2 4 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 75 0 25 0 0 0 0 0 0 0 0.44 0.02 107 | 104 S 1 -1 0 0 -1 0 0 0 -1 -3 -3 0 -2 -3 -1 5 1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.54 0.03 108 | 105 R -2 5 0 -2 -4 1 0 -3 5 -3 -3 2 -2 -3 -2 -1 -1 -3 -1 -3 0 75 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0.68 0.03 109 | 106 K -1 1 -1 -1 -3 1 0 -2 -1 1 -1 4 -1 -2 -2 -1 -1 -3 -2 0 0 0 0 0 0 0 0 0 0 25 0 75 0 0 0 0 0 0 0 0 0.31 0.03 110 | 107 Q -2 3 -1 -2 -3 1 -1 -3 3 -1 -1 0 -1 5 -3 -2 -2 0 2 -2 0 25 0 0 0 13 0 0 13 0 0 0 0 50 0 0 0 0 0 0 0.35 0.02 111 | 108 E -1 -1 0 5 -4 0 3 -2 -1 -3 -4 0 -3 -4 4 0 -1 -4 -3 -3 0 0 0 50 0 0 25 0 0 0 0 0 0 0 25 0 0 0 0 0 0.77 0.02 112 | 109 N -2 0 5 0 -3 0 0 -1 4 -3 -3 2 -2 -3 -2 0 -1 -4 -1 -3 0 0 55 0 0 0 0 0 20 0 0 25 0 0 0 0 0 0 0 0 0.50 0.02 113 | 110 T 0 -1 0 -1 -1 -1 -1 -1 -2 -1 -2 -1 -1 -2 -1 2 5 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 75 0 0 0 0.47 0.03 114 | 111 Q -1 0 -1 -1 -3 5 1 -2 0 -1 -1 1 3 -2 -2 -1 -1 -2 -2 -1 0 0 0 0 0 75 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0.50 0.04 115 | 112 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 116 | 113 V -1 -3 -3 -4 -1 -2 -3 -4 -3 2 2 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 75 0.36 0.02 117 | 114 E -1 0 0 1 -4 2 6 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.83 0.04 118 | 115 Q -1 -1 1 5 -4 2 4 -2 -1 -3 -3 0 -2 -4 -1 0 -1 -4 -3 -3 0 0 0 47 0 13 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0.67 0.02 119 | 116 F -3 -3 -3 -4 -3 -4 -4 -4 -2 0 0 -3 0 7 -4 -3 -2 1 3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0.89 0.04 120 | 117 V -1 -3 -3 -3 -1 -3 -3 -4 -3 3 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 75 0.40 0.02 121 | 118 R -1 5 0 -1 -3 1 0 -2 -1 -3 -3 2 -2 -3 -2 2 0 -3 -2 -3 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0.59 0.03 122 | 119 A 1 1 2 0 -2 2 1 -1 0 -3 -3 2 -1 -3 -1 0 0 -3 -2 -2 25 0 20 0 0 19 10 0 0 0 0 25 0 0 0 0 0 0 0 0 0.29 0.01 123 | 120 G 0 -2 3 -1 -3 -1 -2 5 -1 -4 -4 -1 -3 -3 -2 0 -1 -3 -3 -3 0 0 25 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0.81 0.02 124 | 121 R -1 4 3 0 -3 1 0 -2 0 -3 -3 3 -2 -3 -2 0 -1 -3 -2 -3 0 45 25 0 0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0.50 0.02 125 | 122 T -1 -2 -1 -2 -1 -2 -2 -2 -2 1 -1 -2 -1 -1 -2 0 4 7 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 55 25 0 0 0.53 0.03 126 | 123 N -1 -1 3 3 -3 3 1 2 0 -3 -3 0 -2 -3 -2 0 -1 -3 -3 -3 0 0 25 30 0 25 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0.45 0.02 127 | 124 E -1 0 0 1 -4 2 6 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.83 0.04 128 | 125 L -2 2 -3 -3 -2 -1 -2 -4 -2 1 4 -1 1 0 -3 -2 -1 -2 -1 0 0 25 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0.32 0.02 129 | 126 L -1 2 -2 -2 -2 0 -1 -3 -2 0 2 3 1 -1 -2 -1 -1 -2 -2 0 0 10 0 0 0 0 0 0 0 0 50 40 0 0 0 0 0 0 0 0 0.22 0.02 130 | 127 E -1 1 1 0 -3 3 3 -2 0 -3 -3 3 -2 -3 -1 0 -1 -3 -2 -3 0 0 10 0 0 25 34 0 0 0 0 30 0 0 0 0 0 0 0 0 0.47 0.02 131 | 128 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.62 0.03 132 | 129 K -1 1 -1 0 -3 2 2 -2 -1 -3 -3 3 -2 -4 4 0 -1 -3 -2 -3 0 0 0 0 0 10 20 0 0 0 0 45 0 0 25 0 0 0 0 0 0.58 0.02 133 | 130 V 0 -3 -3 -3 -1 -2 -3 -3 -3 2 2 -2 1 -1 -3 -2 0 -3 -1 3 10 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 65 0.29 0.02 134 | 131 I -1 -3 -3 -3 -1 -3 -3 -4 -3 4 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 45 0 0 0 0 0 0 0 0 0 55 0.39 0.02 135 | 132 G 0 -3 -1 -2 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -3 -3 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.12 0.03 136 | 133 L -2 -3 -4 -4 -2 -3 -3 -4 -3 1 4 -3 2 3 -3 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 25 0 0 0 0 0 0 0.44 0.02 137 | 134 E 0 -1 -1 1 -3 1 5 1 -1 -3 -3 0 -2 -3 -1 0 -1 -3 -2 -2 10 0 0 0 0 0 80 10 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0.03 138 | 135 D -2 3 0 4 -4 1 3 -2 -1 -3 -3 1 -2 -4 -2 0 -1 -4 -3 -3 0 25 0 45 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0.02 139 | 136 T 2 -1 -1 -1 -1 -1 -1 -1 -2 -1 -1 -1 -1 -2 -1 1 4 -3 -2 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0.42 0.03 140 | 137 L -2 -2 -4 -4 -1 -2 -3 -4 -3 1 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.52 0.03 141 | 138 I 1 -3 -3 -3 -1 -2 -3 -2 -3 4 1 -2 1 -1 -2 -1 -1 -3 -2 2 25 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0.28 0.02 142 | 139 A 2 -2 -1 -2 -1 -1 -1 -1 -2 -1 -1 -1 -1 3 -2 1 3 -1 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 50 0 0 0 0.25 0.02 143 | 140 D -1 -2 1 5 -3 -1 1 -2 -2 -1 -2 -1 -2 -3 -2 -1 -1 -4 -3 1 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0.58 0.03 144 | 141 N -1 -1 3 0 -3 1 0 2 6 -4 -3 -1 -2 -2 -2 0 -1 -3 0 -3 0 0 25 0 0 10 0 25 39 0 0 0 0 0 0 0 0 0 0 0 0.48 0.02 145 | 142 I -2 -3 -4 -4 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -3 -1 -3 -1 2 0 0 0 0 0 0 0 0 0 75 25 0 0 0 0 0 0 0 0 0 0.42 0.02 146 | 143 L -2 -3 -4 -4 -2 -3 -3 -4 -3 3 3 -3 1 3 -3 -3 -1 -1 0 1 0 0 0 0 0 0 0 0 0 35 45 0 0 20 0 0 0 0 0 0 0.35 0.01 147 | 144 G 2 -2 -1 -2 -2 -2 -2 5 -2 -3 -3 -2 -2 -3 -2 0 -1 -3 -3 -2 25 0 0 0 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0.78 0.02 148 | 145 K -1 1 0 -1 -3 1 0 2 -1 -3 -3 4 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 0 25 0 0 0 75 0 0 0 0 0 0 0 0 0.47 0.02 149 | 146 Q -1 1 0 -1 -3 6 2 -2 0 -3 -2 1 -1 -4 -2 0 -1 -2 -2 -3 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.79 0.04 150 | 147 S 1 0 0 0 -1 3 0 -1 -1 -3 -3 0 -1 -3 -1 4 1 -3 -2 -2 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0.43 0.03 151 | 148 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 152 | 149 T 0 -2 -1 -2 5 -1 -2 -2 -2 -1 -1 -1 -1 -2 -2 1 4 -3 -2 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0.52 0.03 153 | 150 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.62 0.03 154 | 151 L -2 -3 -4 -4 -2 -3 -3 -4 -3 1 4 -3 2 3 -3 -3 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 25 0 0 0 0 0 0 0.44 0.02 155 | 152 A 4 -1 -1 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 2 0 -3 -2 -1 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0.40 0.02 156 | 153 N -2 -1 6 1 -3 0 0 -1 0 -4 -4 0 -2 -3 -2 0 0 -4 -2 -3 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.85 0.04 157 | 154 M -1 -2 -3 -4 -2 -1 -2 -3 -2 1 2 -2 7 0 -3 -2 -1 -2 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0.55 0.05 158 | 155 L -1 -3 -3 -4 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 55 25 0 0 0 0 0 0 0 0 20 0.37 0.02 159 | 156 V -1 -3 -3 -3 -1 -3 -3 -4 -3 3 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 75 0.40 0.02 160 | 157 K -1 4 0 -1 -3 1 0 -2 -1 -2 -2 3 -1 -3 -2 0 2 -3 -2 -2 0 50 0 0 0 0 0 0 0 0 0 25 0 0 0 0 25 0 0 0 0.45 0.02 161 | 158 D -2 -1 2 5 -4 0 3 -2 -1 -3 -4 0 -3 -4 -2 0 -1 -4 -3 -3 0 0 10 65 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0.74 0.02 162 | 159 E -1 -1 0 3 -3 1 3 -2 0 -3 -3 1 -2 0 -2 -1 -1 -1 3 -2 0 0 0 29 0 0 35 0 0 0 0 10 0 0 0 0 0 0 25 0 0.42 0.02 163 | 160 G -1 -1 0 3 -3 2 0 4 -1 -4 -4 -1 -2 -4 -2 0 -1 -3 -3 -3 0 0 0 25 0 20 0 55 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0.02 164 | 161 D -2 -1 2 5 -4 0 2 -2 4 -3 -4 -1 -3 -3 -2 0 -1 -4 -1 -3 0 0 9 55 0 0 10 0 25 0 0 0 0 0 0 0 0 0 0 0 0.63 0.02 165 | 162 T -1 2 -1 -1 -2 1 0 -2 0 -2 -2 2 -1 0 -2 0 2 -1 3 -1 0 10 0 0 0 9 0 0 0 0 0 30 0 0 0 0 25 0 25 0 0.26 0.02 166 | 163 L -2 -2 -3 -4 -2 -2 -3 -4 -1 1 4 -3 1 1 -3 -2 -1 0 4 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 0 0 25 0 0.41 0.02 167 | 164 V -1 -3 -3 -3 -1 -3 -3 -4 -3 3 1 -3 1 -1 -3 -2 0 -3 -1 4 0 0 0 0 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 70 0.39 0.02 168 | 165 F -2 -3 -3 -4 -2 -3 -3 -3 -2 1 0 -3 0 6 -4 -2 -2 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 75 0 0 0 0 0 25 0.57 0.03 169 | 166 S 0 -1 0 -1 -1 -1 -1 3 -2 -2 -2 -1 -1 -3 -1 2 4 -3 -2 -1 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 25 50 0 0 0 0.38 0.02 170 | 167 N 0 -1 3 -1 -1 -1 -1 -1 -1 0 -1 -1 -1 -2 -2 2 3 -3 -2 1 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 20 29 0 0 25 0.22 0.01 171 | 168 I -2 -3 -4 -3 -1 -3 -4 -4 -4 5 1 -3 1 0 -3 -3 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.49 0.03 172 | 169 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 173 | 170 H -2 -1 2 -1 -3 0 0 -2 8 -4 -3 -1 -2 -2 -3 -1 -2 -3 1 -4 0 0 10 0 0 0 0 0 90 0 0 0 0 0 0 0 0 0 0 0 0.95 0.04 174 | 171 E -1 0 0 1 -4 2 6 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.83 0.04 175 | 172 R -2 5 -1 -2 -3 0 -1 -3 -1 -1 1 1 0 -2 -3 -1 -1 -3 -2 -1 0 75 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0.50 0.03 176 | 173 A 4 -1 -1 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 2 0 -3 -2 -1 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0.40 0.02 177 | 174 N 0 -2 3 -1 -2 -2 -2 2 -2 1 -1 -2 -1 -2 -2 -1 0 -3 -2 2 0 0 25 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 50 0.20 0.02 178 | 175 L -1 -2 2 -1 -1 -1 -2 -2 -2 1 1 -1 0 -1 -2 0 2 -3 -2 2 0 0 20 0 0 0 0 0 0 0 25 0 0 0 0 0 29 0 0 25 0.16 0.01 179 | 176 P 0 -2 -1 -1 -2 -1 -1 -2 -2 -3 -3 -1 -2 -4 7 2 0 -4 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 75 25 0 0 0 0 1.45 0.03 180 | 177 T 0 -2 -1 -2 -1 -1 -1 -2 -2 -1 -1 -1 -1 3 -2 1 4 -1 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 10 65 0 0 0 0.33 0.02 181 | 178 F -2 -3 -4 -4 -2 -3 -3 -3 -2 1 1 -3 0 5 -4 -3 -2 7 2 0 0 0 0 0 0 0 0 0 0 9 20 0 0 45 0 0 0 25 0 0 0.70 0.02 182 | 179 S 0 2 0 -1 -2 0 0 1 -1 -3 -3 2 -2 -3 -1 3 0 -3 -2 -2 0 10 0 0 0 0 0 10 0 0 0 25 0 0 0 54 0 0 0 0 0.32 0.02 183 | 180 L 1 -3 -3 -3 -2 -3 -3 -2 -2 0 1 -2 0 5 -3 -1 -2 0 2 -1 25 0 0 0 0 0 0 0 0 0 13 0 0 62 0 0 0 0 0 0 0.40 0.02 184 | 181 F -3 -3 -3 -4 -3 -4 -4 -4 -2 0 0 -3 0 7 -4 -3 -2 1 3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0.89 0.04 185 | 182 N -2 -1 5 0 -3 0 0 -1 6 -4 -3 -1 -2 -2 -2 0 -1 -3 0 -3 0 0 50 0 0 0 0 0 50 0 0 0 0 0 0 0 0 0 0 0 0.69 0.03 186 | 183 S 0 -1 0 -1 -1 -1 0 -1 -1 -2 -2 -1 -2 -2 5 2 0 -2 -2 -2 2 1 1 1 0 1 2 2 1 1 2 1 1 1 41 37 1 0 1 2 0.64 0.01 187 | 184 G 0 -1 0 -1 -1 -1 -1 3 -1 -1 -2 -1 -1 -2 -1 1 3 -2 -2 -1 2 1 1 1 0 1 2 27 1 1 2 1 1 1 1 12 41 0 1 2 0.25 0.01 188 | 185 Q 0 3 0 -1 -2 3 0 -2 -1 -3 -2 1 -1 -3 3 1 1 -3 -2 -2 0 25 0 0 0 25 0 0 0 0 0 0 0 0 20 20 9 0 0 0 0.44 0.01 189 | 186 R -1 4 -1 -2 -3 0 -1 -3 -1 -3 -3 1 -2 -4 6 -1 -1 -3 -3 -3 0 50 0 0 0 0 0 0 0 0 0 0 0 0 50 0 0 0 0 0 1.03 0.03 190 | 187 R -1 3 -1 -1 -2 0 2 -2 -1 1 -1 0 -1 -2 -2 0 2 -3 -2 0 0 25 0 0 0 0 25 0 0 20 0 0 0 0 0 0 29 0 0 0 0.20 0.01 191 | 188 Y -2 -2 -3 -4 -2 -2 -3 -4 1 0 1 -2 0 2 -3 -2 -2 1 7 -1 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 75 0 0.68 0.03 192 | 189 P -1 -2 -1 -2 -2 -1 -1 -2 -2 -2 -2 -1 -2 -3 6 0 3 -3 -3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 55 0 45 0 0 0 1.03 0.03 193 | 190 T -1 0 -1 -2 -1 -1 -1 -2 -2 1 -1 1 0 -2 -2 0 4 -3 -2 0 0 0 0 0 0 0 0 0 0 22 0 20 0 0 0 0 57 0 0 0 0.24 0.02 194 | 191 S 0 -1 4 3 -2 0 0 -1 0 -3 -3 0 -2 -3 -2 2 0 -4 -2 -3 0 0 40 25 0 0 0 0 0 0 0 0 0 0 0 34 0 0 0 0 0.49 0.02 195 | 192 A 1 1 -1 -2 -2 0 0 -1 -1 -2 -1 3 -1 3 -2 0 -1 -2 0 -1 25 0 0 0 0 0 0 0 0 0 0 50 0 25 0 0 0 0 0 0 0.21 0.02 196 | 193 H -1 -1 3 -1 -2 1 0 -1 3 -2 -1 -1 -1 -1 -2 1 0 6 0 -2 0 0 25 0 0 13 0 0 13 0 10 0 0 0 0 20 0 19 0 0 0.37 0.02 197 | 194 E 1 -1 -1 0 -2 0 2 2 -2 -1 -2 -1 -1 -3 -2 0 2 -3 -2 0 10 0 0 0 0 0 25 25 0 0 0 0 0 0 0 0 31 0 0 9 0.24 0.01 198 | 195 L -2 -2 -4 -4 -1 -2 -3 -4 -3 1 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.52 0.03 199 | 196 V -1 -3 -3 -3 -1 -3 -3 -4 -4 4 1 -3 1 0 -3 -2 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 77 0 0 0 0 0 0 0 0 0 23 0.43 0.02 200 | 197 S 1 4 0 -1 -2 0 0 -1 -1 -3 -2 1 -2 -3 -2 2 0 -3 -2 -2 13 50 0 0 0 0 0 0 0 0 0 0 0 0 0 38 0 0 0 0 0.40 0.02 201 | 198 G 0 -2 0 -1 -2 -1 -1 3 0 -3 -2 -1 -2 0 -2 3 0 -1 3 -2 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 50 0 0 25 0 0.34 0.02 202 | 199 I -2 -3 -4 -3 -1 -3 -4 -4 -4 5 1 -3 1 0 -3 -3 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.49 0.03 203 | 200 A 1 3 2 -1 -2 0 0 -1 5 -3 -3 0 -2 -2 -2 0 -1 -3 0 -2 25 25 20 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0.33 0.02 204 | 201 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 205 | 202 L -2 -2 -4 -4 -1 -2 -3 -4 -3 1 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.52 0.03 206 | 203 Y -1 -1 3 -1 -3 0 -1 2 6 -3 -3 -1 -2 -1 -2 0 -1 -2 2 -3 0 0 19 0 0 0 0 20 38 0 0 0 0 0 0 10 0 0 13 0 0.41 0.02 207 | 204 E -1 0 3 1 -4 1 5 -2 0 -4 -3 0 -2 -3 -2 0 -1 -3 -2 -3 0 0 25 0 0 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0.64 0.03 208 | 205 P -1 0 -1 -1 -3 2 0 2 -1 -3 -3 2 -2 -4 4 0 -1 -3 -2 -3 0 0 0 0 0 20 0 25 0 0 0 29 0 0 25 0 0 0 0 0 0.52 0.02 209 | 206 S 0 -1 3 0 -2 0 -1 -1 -1 -3 -3 -1 -2 -3 4 3 1 -3 -2 -2 0 0 19 0 0 0 0 0 0 0 0 0 0 0 25 55 0 0 0 0 0.55 0.02 210 | 207 D -2 -1 0 4 -4 1 4 -2 4 -3 -3 0 -2 -3 -2 0 -1 -3 -1 -3 0 0 0 35 0 0 40 0 25 0 0 0 0 0 0 0 0 0 0 0 0.59 0.02 211 | 208 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 212 | 209 N -2 0 6 1 -3 0 0 -1 0 -3 -3 2 -2 -3 -2 0 0 -4 -2 -3 0 0 75 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0.61 0.03 213 | 210 R -1 3 0 -1 -3 1 0 -2 6 -3 -3 0 -2 -3 4 -1 -1 -3 0 -3 0 25 0 0 0 10 0 0 40 0 0 0 0 0 25 0 0 0 0 0 0.63 0.02 214 | 211 S 3 -2 -1 -2 -1 -1 -1 -1 -2 0 -1 -1 -1 -2 -1 2 0 -3 -2 1 50 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 25 0.24 0.02 215 | 212 G 0 -3 -1 -2 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2 -3 -3 -4 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 1.12 0.03 216 | 213 L -2 -2 -3 -4 -2 -2 -3 -4 -3 1 4 -2 4 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 75 0 25 0 0 0 0 0 0 0 0.44 0.02 217 | 214 A 4 -2 -1 -2 -1 -1 -1 0 -2 -1 -2 -1 -1 -2 -1 1 2 -3 -2 0 75 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0.37 0.02 218 | 215 G 0 -2 0 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 1 -1 -3 -3 -3 0 0 0 0 0 0 0 90 0 0 0 0 0 0 0 10 0 0 0 0 0.96 0.03 219 | 216 D -2 -2 1 6 -4 -1 1 -2 -1 -4 -4 -1 -3 -4 -2 0 -1 -5 -3 -4 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.04 0.04 220 | 217 K 0 0 -2 -2 -3 -1 -1 -2 -2 -3 -3 2 -2 -4 7 -1 -1 -4 -3 -2 10 0 0 0 0 0 0 0 0 0 0 25 0 0 65 0 0 0 0 0 1.19 0.03 221 | 218 R -2 6 -1 -2 -4 1 0 -3 0 -3 -2 2 -2 -3 -2 -1 -1 -3 -2 -3 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.86 0.04 222 | 219 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.48 0.03 223 | 220 K -1 1 2 -1 -3 1 0 -2 5 -3 -3 4 -2 -3 -2 0 -1 -3 -1 -3 0 0 10 0 0 0 0 0 25 0 0 65 0 0 0 0 0 0 0 0 0.45 0.02 224 | 221 E -1 0 0 1 -4 2 6 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.83 0.04 225 | 222 F -3 -3 -3 -4 -3 -4 -4 -4 -2 0 0 -3 0 7 -4 -3 -2 1 3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0.89 0.04 226 | 223 G 2 1 -1 -2 3 -1 -2 4 -2 -3 -3 -1 -2 -3 -2 0 -1 -3 -3 -2 25 13 0 0 10 0 0 52 0 0 0 0 0 0 0 0 0 0 0 0 0.47 0.02 227 | 224 E -1 0 4 1 -3 1 4 -2 0 -3 -3 2 -2 -3 -2 0 -1 -3 -2 -3 0 0 34 0 0 0 45 0 0 0 0 21 0 0 0 0 0 0 0 0 0.49 0.02 228 | 225 V -1 -3 -3 -4 -1 -3 -3 -4 -3 2 2 -3 1 3 -3 -2 -1 -1 0 3 0 0 0 0 0 0 0 0 0 0 29 0 0 25 0 0 0 0 0 45 0.30 0.01 229 | 226 A 4 -2 -2 -2 -1 -1 -1 0 -2 -1 -1 -1 -1 -2 -1 1 0 -3 -2 1 90 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 0.40 0.03 230 | 227 T -1 -1 3 0 -2 0 2 -2 -1 -1 0 0 1 -2 -2 0 1 -3 -2 0 0 0 25 0 0 0 30 0 0 0 10 0 13 0 0 0 13 0 0 9 0.18 0.01 231 | 228 K 0 3 2 -1 -2 1 0 -1 -1 -3 -3 2 -2 -3 -1 2 0 -3 -2 -2 0 25 10 0 0 0 0 0 0 0 0 25 0 0 0 40 0 0 0 0 0.35 0.02 232 | 229 V 0 -2 -2 -2 -1 -2 -2 -2 -3 2 0 -2 0 -1 -2 1 0 -3 -2 3 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 25 0 0 0 65 0.23 0.02 233 | 230 I -1 -2 -3 -3 -2 -1 -3 -3 -2 2 2 -2 6 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 23 0 0 77 0 0 0 0 0 0 0 0.43 0.04 234 | 231 K -1 0 3 4 -3 0 2 -1 -1 -3 -3 1 -2 -3 -2 1 0 -4 -3 -3 0 0 20 35 0 0 19 0 0 0 0 13 0 0 0 13 0 0 0 0 0.47 0.01 235 | 232 Q -1 0 3 3 -3 2 1 -1 0 -3 -3 2 -2 -3 -2 1 0 -3 -2 -3 0 0 30 19 0 13 0 0 0 0 0 25 0 0 0 13 0 0 0 0 0.39 0.01 236 | 233 E -1 1 0 0 -3 3 3 -2 0 -2 -1 2 -1 -3 -1 1 -1 -3 -2 -2 0 0 0 0 0 25 35 0 0 0 10 19 0 0 0 10 0 0 0 0 0.35 0.01 237 | 234 K 1 0 0 2 -2 0 0 1 -2 -1 -2 2 -1 -3 -1 0 -1 -3 -2 -1 25 0 0 20 0 0 0 13 0 10 0 32 0 0 0 0 0 0 0 0 0.18 0.01 238 | 235 I -2 -3 -4 -3 -1 -3 -4 -4 -4 5 1 -3 1 0 -3 -3 -1 -3 -2 3 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0.49 0.03 239 | 236 K -1 0 2 4 -3 0 0 -2 -1 0 -2 2 -1 -3 -2 -1 -1 -4 -2 1 0 0 10 39 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 25 0.27 0.01 240 | 237 S -1 -1 4 4 -3 0 1 -1 -1 -3 -4 -1 -3 -3 -2 2 0 -4 -3 -3 0 0 30 45 0 0 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0.55 0.02 241 | 238 A 1 -2 -2 -3 -2 -2 -2 -2 0 0 1 -2 0 2 -2 -1 -1 1 5 0 25 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 0 50 0 0.35 0.02 242 | 239 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -2 -1 -2 -1 3 -3 -2 -2 2 7 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 1.04 0.04 243 | 240 E 0 0 -1 0 -2 3 3 -2 -1 -1 1 0 0 -2 -2 0 -1 -2 -2 -1 13 0 0 0 0 30 32 0 0 0 25 0 0 0 0 0 0 0 0 0 0.26 0.02 244 | 241 K -1 3 0 -1 -3 1 0 -2 -1 -2 -2 4 -1 -3 -1 0 2 -3 -2 -2 0 13 0 0 0 0 0 0 0 0 0 62 0 0 0 0 25 0 0 0 0.40 0.02 245 | 242 V -1 -3 -3 -4 -1 -3 -3 -4 -3 3 2 -3 1 0 -3 -2 -1 -3 -1 3 0 0 0 0 0 0 0 0 0 25 29 0 0 0 0 0 0 0 0 45 0.34 0.01 246 | 243 A 5 -2 -2 -2 -1 -1 -1 0 -2 -2 -2 -1 -1 -3 -1 1 0 -3 -2 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.48 0.03 247 | 244 N 0 1 3 -1 -2 -1 -1 -2 -1 1 -1 0 -1 -2 -2 0 3 -3 -2 0 10 10 25 0 0 0 0 0 0 19 0 0 0 0 0 0 35 0 0 0 0.18 0.01 248 | 245 A 3 -1 3 -1 -1 -1 -1 0 -1 -2 -2 -1 -1 -3 -1 1 2 -3 -2 -1 55 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0 20 0 0 0 0.30 0.02 249 | 246 D -2 -1 5 5 -3 0 1 -1 0 -4 -4 -1 -3 -4 -2 0 -1 -4 -3 -3 0 0 50 50 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.73 0.03 250 | 247 I -2 -3 -4 -4 -1 -3 -3 -4 -3 3 3 -3 2 0 -3 -3 -1 -2 -1 2 0 0 0 0 0 0 0 0 0 50 50 0 0 0 0 0 0 0 0 0 0.40 0.02 251 | 248 D -1 -1 2 4 -2 0 1 -1 -1 -2 -3 -1 -2 -3 -1 2 2 -4 -2 -2 0 0 9 45 0 0 0 0 0 0 0 0 0 0 0 20 25 0 0 0 0.45 0.02 252 | 249 S 0 -2 -1 -1 -2 -1 -1 -1 -2 -3 -3 -1 -2 -3 6 3 0 -4 -3 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 55 45 0 0 0 0 1.03 0.03 253 | 250 V 0 -2 -2 -3 -1 -2 -2 -3 -3 2 1 -2 1 -1 -2 -1 2 -3 -1 3 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 25 0 0 62 0.26 0.02 254 | 251 Y -2 -2 -3 -3 -2 -2 -2 -4 -1 3 1 0 1 1 -3 -2 -1 -1 3 1 0 0 0 0 0 0 0 0 0 54 10 10 0 0 0 0 0 0 25 0 0.24 0.02 255 | 252 K 2 -1 2 3 -2 0 0 -1 -1 -3 -3 1 -2 -3 -1 2 0 -3 -2 -2 25 0 13 29 0 0 0 0 0 0 0 13 0 0 0 20 0 0 0 0 0.31 0.01 256 | 253 K -1 2 0 0 -3 4 2 -2 0 -3 -3 4 -1 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 39 10 0 0 0 0 50 0 0 0 0 0 0 0 0 0.52 0.02 257 | 254 C -1 -3 -3 -4 9 -3 -4 -3 -3 0 1 -3 0 -2 -3 -1 -1 -2 -2 -1 0 0 0 0 75 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0.95 0.04 258 | 255 S 0 0 3 1 -3 1 4 -1 0 -3 -3 0 -2 -3 -1 2 0 -3 -2 -3 0 0 29 0 0 0 45 0 0 0 0 0 0 0 0 25 0 0 0 0 0.46 0.02 259 | 256 S 0 3 0 0 -3 1 2 -2 -1 -3 -3 3 -2 -3 -1 2 0 -3 -2 -2 0 19 0 0 0 0 25 0 0 0 0 31 0 0 0 25 0 0 0 0 0.38 0.01 260 | 257 L -2 -2 -4 -4 -1 -2 -3 -4 -3 1 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.52 0.03 261 | 258 S 3 -1 0 -1 -1 -1 -1 0 -1 -2 -2 -1 -1 -3 -1 3 1 -3 -2 -1 50 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 0 0 0 0 0.39 0.02 262 | 259 Q -1 2 -1 0 -3 2 3 -2 -1 -1 -2 3 -1 -3 -1 -1 -1 -3 -2 -1 0 13 0 0 0 13 25 0 0 10 0 39 0 0 0 0 0 0 0 0 0.35 0.01 263 | 260 N 3 -1 3 0 -1 0 1 0 -1 -2 -2 0 -2 -3 -1 1 0 -3 -2 -1 53 0 34 0 0 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0.30 0.01 264 | 261 S 1 -1 1 0 -1 0 0 0 -1 -3 -3 0 -2 -3 -1 4 1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0.50 0.02 265 | 262 T -1 0 4 0 -2 0 0 -1 0 -2 -2 2 -2 -3 -2 1 3 -3 -2 -2 0 0 39 0 0 0 0 0 0 0 0 27 0 0 0 0 34 0 0 0 0.35 0.01 266 | 263 F -1 1 -1 -2 -2 -1 -1 2 -1 -1 -1 -1 -1 4 -2 0 -1 -1 1 -2 1 14 1 1 0 1 1 26 0 1 1 1 0 35 1 14 1 0 0 1 0.19 0.00 267 | 264 F -2 -2 -3 -3 -2 -2 -2 -3 -2 1 3 -2 1 4 -2 -2 -1 0 1 0 1 1 1 1 0 1 1 1 0 1 53 1 0 35 1 1 1 0 0 1 0.30 0.01 268 | 265 G 0 -2 -1 -2 -1 -2 -2 3 -2 1 0 -2 0 -1 -2 -1 -1 -2 -2 2 1 1 1 1 0 1 1 35 0 1 1 1 0 1 1 1 1 0 0 53 0.22 0.01 269 | 266 G 0 1 0 -1 -3 2 0 4 -1 -3 -3 3 -2 -3 -2 0 -1 -3 -2 -3 0 0 0 0 0 13 0 48 0 0 0 39 0 0 0 0 0 0 0 0 0.47 0.01 270 | 267 K -1 1 0 -1 -3 2 0 -2 3 -2 0 3 -1 -2 -1 1 -1 -3 -1 -2 0 0 0 0 0 13 0 0 12 0 13 48 0 0 0 13 0 0 0 0 0.24 0.01 271 | 268 N 0 1 4 0 -2 0 1 1 0 -3 -3 0 -2 -3 -2 2 0 -3 -2 -3 0 13 34 0 0 0 13 14 0 0 0 0 0 0 0 25 0 0 0 0 0.34 0.01 272 | 269 N -2 -1 4 5 -3 0 1 -1 -1 -3 -4 -1 -3 -4 -2 0 -1 -4 -3 -3 0 0 34 66 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.75 0.01 273 | 270 C -1 -4 -3 -4 9 -3 -4 -3 -3 -1 -2 -3 -2 -3 -3 -1 -1 -3 -3 -1 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.35 0.03 274 | 271 N 1 -2 2 2 -1 -1 -1 -2 -2 1 -1 -1 -1 -2 -2 0 1 -3 -2 2 13 0 17 17 0 0 0 0 0 0 0 0 0 0 0 0 14 0 0 39 0.14 0.01 275 | 272 A 2 -2 -1 -2 -2 -2 -2 5 -2 -3 -3 -1 -2 -3 -2 0 -1 -3 -3 -2 34 0 0 0 0 0 0 66 0 0 0 0 0 0 0 0 0 0 0 0 0.66 0.01 276 | 273 Y -2 -2 -2 -3 -3 -2 -2 -3 2 -2 -1 -2 -1 3 -3 -2 -2 2 7 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0.96 0.02 277 | 274 R -1 2 0 0 -3 5 3 -2 0 -3 -3 1 -1 -3 -2 0 -1 -3 -2 -3 0 17 0 0 0 56 27 0 0 0 0 0 0 0 0 0 0 0 0 0 0.56 0.01 278 | 275 Q -1 -1 -1 -1 -2 3 0 -2 -1 0 1 0 0 1 -2 1 1 -2 0 -1 0 0 0 0 0 34 0 0 0 0 26 0 0 12 0 13 14 0 0 0 0.15 0.01 279 | 276 Y -2 -3 -3 -4 -3 -3 -3 -3 0 -1 0 -3 0 6 -4 -2 -2 1 5 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 66 0 0 0 0 34 0 0.73 0.02 280 | 277 F -2 -3 -3 -4 -3 -3 -4 -3 -1 0 0 -3 0 7 -4 -3 -2 1 3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0.82 0.02 281 | 278 K -1 2 0 0 -3 1 2 -2 -1 -3 -3 5 -2 -3 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 14 0 0 0 0 86 0 0 0 0 0 0 0 0 0.52 0.02 282 | 279 E -1 0 0 2 -4 2 5 -2 0 -4 -3 1 -2 -4 -1 0 -1 -3 -2 -3 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0.79 0.02 283 | 280 I -1 -2 -3 -3 -2 -1 -3 -3 -2 3 2 -2 5 0 -3 -2 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 34 0 0 66 0 0 0 0 0 0 0 0.35 0.02 284 | 281 Q -1 1 0 0 -3 6 2 -2 0 -3 -2 1 -1 -4 -1 0 -1 -2 -2 -2 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.73 0.02 285 | 282 K -1 4 0 -1 -3 1 1 -2 -1 -3 -3 4 -2 -3 -1 0 -1 -3 -2 -3 0 27 0 0 0 0 0 0 0 0 0 73 0 0 0 0 0 0 0 0 0.55 0.01 286 | 283 E -1 2 3 3 -3 1 2 -1 0 -3 -3 2 -2 -3 -2 0 -1 -4 -2 -3 0 13 27 17 0 0 17 0 0 0 0 26 0 0 0 0 0 0 0 0 0.40 0.01 287 | 284 A 4 -2 -2 -2 -1 -1 -1 0 -2 -1 -2 -1 -1 -2 -1 1 0 -3 -2 0 100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.44 0.02 288 | 285 A 3 2 -1 -2 -2 0 -1 3 -1 -2 -2 0 -2 -3 -2 0 -1 -3 -2 -1 49 26 0 0 0 0 0 25 0 0 0 0 0 0 0 0 0 0 0 0 0.31 0.00 289 | 286 D -1 -1 1 5 -4 1 4 -2 -1 -3 -3 0 -3 -4 -1 0 -1 -4 -3 -3 0 0 0 49 0 0 51 0 0 0 0 0 0 0 0 0 0 0 0 0 0.70 0.01 290 | 287 T -1 0 -1 -1 -2 4 1 -2 -1 1 -1 0 0 -2 -2 0 2 -2 -2 0 0 0 0 0 0 51 0 0 0 25 0 0 0 0 0 0 24 0 0 0 0.24 0.01 291 | 288 V 0 -2 -2 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -1 2 -3 -1 3 0 0 0 0 0 0 0 0 0 25 0 0 0 0 0 0 26 0 0 49 0.25 0.00 292 | 289 S 0 -1 0 1 -2 1 3 -1 -1 -3 -3 0 -2 -3 -1 3 1 -3 -2 -2 0 0 0 0 0 0 40 0 0 0 0 0 0 0 0 60 0 0 0 0 0.41 0.00 293 | 290 K 0 1 0 -1 -2 1 0 -1 -1 -3 -3 4 -2 -3 -1 2 0 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 60 0 0 0 40 0 0 0 0 0.36 0.00 294 | 291 F -2 -3 -3 -4 -3 -3 -3 -3 -1 0 0 -3 0 7 -4 -3 -2 1 3 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0.76 0.01 295 | 292 D -1 -1 1 5 -4 1 4 -2 -1 -3 -4 0 -3 -4 -1 0 -1 -4 -3 -3 0 0 0 60 0 0 40 0 0 0 0 0 0 0 0 0 0 0 0 0 0.72 0.00 296 | 293 L -2 -2 -4 -4 -1 -2 -3 -4 -3 2 4 -3 2 0 -3 -3 -1 -2 -1 1 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0 0.45 0.00 297 | 294 K -1 2 0 -1 -3 1 1 -2 -1 -3 -3 5 -1 -3 -1 0 -1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 100 0 0 0 0 0 0 0 0 0.51 0.00 298 | 295 K -1 2 0 -1 -3 1 1 -1 -1 -3 -2 4 -1 -3 -1 0 -1 -3 -2 -2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.00 0.00 299 | 300 | K Lambda 301 | Standard Ungapped 0.1289 0.3115 302 | Standard Gapped 0.0410 0.2670 303 | PSI Ungapped 0.1330 0.3179 304 | PSI Gapped 0.0407 0.2670 305 | --------------------------------------------------------------------------------