├── Validation ├── Validation_1_Background.fasta.fai ├── Validation_1_Input.fasta ├── Validation_1_Input_Aligned.fasta └── Validation_1_Background.fasta ├── setup.py ├── meta.yaml ├── PrimedRPA.yml ├── README.md ├── PrimedRPA_Parameters.txt ├── LICENSE └── PrimedRPA /Validation/Validation_1_Background.fasta.fai: -------------------------------------------------------------------------------- 1 | AF033819.3 910 35 70 71 2 | -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | import setuptools 2 | 3 | setuptools.setup( 4 | name="primedrpa", 5 | version="1.0.0", 6 | license="GPL3", 7 | packages=setuptools.find_packages(), 8 | long_description="RPA Primer & Probe Design Tool", 9 | scripts= ['PrimedRPA']) 10 | -------------------------------------------------------------------------------- /Validation/Validation_1_Input.fasta: -------------------------------------------------------------------------------- 1 | >Seq1 2 | GATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTCGTCTGGCGGCTGTGCACG 3 | CGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGAAGTA 4 | >Seq2 5 | NNNGATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTCGTCTGGCGGCTGTGCACG 6 | CGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGAAGTANNN 7 | -------------------------------------------------------------------------------- /Validation/Validation_1_Input_Aligned.fasta: -------------------------------------------------------------------------------- 1 | >Seq1 2 | ---GATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTAT 3 | TTCGTCTGGCGGCTGTGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATG 4 | TCGCAGTATCTGTCTTTGAAGTA--- 5 | >Seq2 6 | NNNGATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTAT 7 | TTCGTCTGGCGGCTGTGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATG 8 | TCGCAGTATCTGTCTTTGAAGTANNN 9 | -------------------------------------------------------------------------------- /meta.yaml: -------------------------------------------------------------------------------- 1 | {% set name = "primedrpa" %} 2 | {% set version = "1.0.1" %} 3 | {% set sha256 = "f622eaac1c28e874cb829663b6ce377c7da10ce5ec16010b8d447e19eea29faa" %} 4 | 5 | package: 6 | name: {{name}} 7 | version: {{version}} 8 | 9 | 10 | source: 11 | url: https://github.com/MatthewHiggins2017/bioconda-PrimedRPA/archive/1.0.1.tar.gz 12 | sha256: '{{sha256}}' 13 | 14 | build: 15 | script: python -m pip install --no-deps --ignore-installed . 16 | noarch: python 17 | number: 0 18 | 19 | requirements: 20 | host: 21 | - python >=3.5 22 | - pip 23 | run: 24 | - python >=3.5 25 | - pandas 26 | - clustalo 27 | - samtools 28 | - blast 29 | 30 | test: 31 | commands: 32 | - PrimedRPA --help 33 | 34 | about: 35 | home: https://github.com/MatthewHiggins2017/bioconda-PrimedRPA/ 36 | license: GPL3 37 | license_file: LICENSE 38 | summary: RPA primer & probe design tool. 39 | -------------------------------------------------------------------------------- /Validation/Validation_1_Background.fasta: -------------------------------------------------------------------------------- 1 | >AF033819.3 HIV-1, complete genome 2 | GGTCTCTCTGGTTAGACCAGATCTGAGCCTGGGAGCTCTCTGGCTAACTAGGGAACCCACTGCTTAAGCC 3 | TCAATAAAGCTTGCCTTGAGTGCTTCAAGTAGTGTGTGCCCGTCTGTTGTGTGACTCTGGTAACTAGAGA 4 | TCCCTCAGACCCTTTTAGTCAGTGTGGAAAATCTCTAGCAGTGGCGCCCGAACAGGGACCTGAAAGCGAA 5 | AGGGAAACCAGAGGAGCTCTCTCGACGCAGGACTCGGCTTGCTGAAGCGCGCACGGCAAGAGGCGAGGGG 6 | CGGCGACTGGTGAGTACGCCAAAAATTTTGACTAGCGGAGGCTAGAAGGAGAGAGATGGGTGCGAGAGCG 7 | TCAGTATTAAGCGGGGGAGAATTAGATCGATGGGAAAAAATTCGGTTAAGGCCAGGGGGAAAGAAAAAAT 8 | ATAAATTAAAACATATAGTATGGGCAAGCAGGGAGCTAGAACGATTCGCAGTTAATCCTGGCCTGTTAGA 9 | AACATCAGAAGGCTGTAGACAAATACTGGGACAGCTACAACCATCCCTTCAGACAGGATCAGAAGAACTT 10 | AGATCATTATATAATACAGTAGCAACCCTCTATTGTGTGCATCAAAGGATAGAGATAAAAGACACCAAGG 11 | AAGCTTTAGACAAGATAGAGGAAGAGCAAAACAAAAGTAAGAAAAAAGCACAGCAAGCAGCAGCTGACAC 12 | AGGACACAGCAATCAGGTCAGCCAAAATTACCCTATAGTGCAGAACATCCAGGGGCAAATGGTACATCAG 13 | GCCATATCACCTAGAACTTTAAATGCATGGGTAAAAGTAGTAGAAGAGAAGGCTTTCAGCCCAGAAGTGA 14 | TACCCATGTTTTCAGCATTATCAGAAGGAGCCACCCCACAAGATTTAAACACCATGCTAAACACAGTGGG 15 | -------------------------------------------------------------------------------- /PrimedRPA.yml: -------------------------------------------------------------------------------- 1 | name: RPA 2 | channels: 3 | - conda-forge 4 | - bioconda 5 | - defaults 6 | dependencies: 7 | - _libgcc_mutex=0.1 8 | - _openmp_mutex=5.1 9 | - blas=1.0 10 | - blast=2.12.0 11 | - bzip2=1.0.8 12 | - c-ares=1.18.1 13 | - ca-certificates=2022.6.15 14 | - certifi=2021.5.30 15 | - clustalo=1.2.3 16 | - curl=7.82.0 17 | - entrez-direct=16.2 18 | - htslib=1.10.2 19 | - intel-openmp=2022.0.1 20 | - krb5=1.19.2 21 | - ld_impl_linux-64=2.38 22 | - libcurl=7.82.0 23 | - libdeflate=1.6 24 | - libedit=3.1.20210714 25 | - libev=4.33 26 | - libffi=3.3 27 | - libgcc-ng=11.2.0 28 | - libgomp=11.2.0 29 | - libidn2=2.3.2 30 | - libnghttp2=1.46.0 31 | - libssh2=1.10.0 32 | - libstdcxx-ng=11.2.0 33 | - libunistring=0.9.10 34 | - mkl=2020.2 35 | - mkl-service=2.3.0 36 | - mkl_fft=1.3.0 37 | - mkl_random=1.1.1 38 | - ncurses=6.2 39 | - numpy=1.19.2 40 | - numpy-base=1.19.2 41 | - openssl=1.1.1o 42 | - pandas=1.1.5 43 | - pcre=8.45 44 | - perl=5.26.2 45 | - perl-archive-tar=2.32 46 | - perl-carp=1.38 47 | - perl-common-sense=3.74 48 | - perl-compress-raw-bzip2=2.087 49 | - perl-compress-raw-zlib=2.087 50 | - perl-exporter=5.72 51 | - perl-exporter-tiny=1.002001 52 | - perl-extutils-makemaker=7.36 53 | - perl-io-compress=2.087 54 | - perl-io-zlib=1.10 55 | - perl-json=4.02 56 | - perl-json-xs=2.34 57 | - perl-list-moreutils=0.428 58 | - perl-list-moreutils-xs=0.428 59 | - perl-pathtools=3.75 60 | - perl-scalar-list-utils=1.52 61 | - perl-types-serialiser=1.0 62 | - perl-xsloader=0.24 63 | - pip=21.2.2 64 | - python=3.6.13 65 | - python-dateutil=2.8.2 66 | - python_abi=3.6 67 | - pytz=2021.3 68 | - readline=8.1 69 | - samtools=1.10 70 | - setuptools=58.0.4 71 | - six=1.16.0 72 | - sqlite=3.38.5 73 | - tk=8.6.12 74 | - wget=1.21.3 75 | - wheel=0.37.1 76 | - xz=5.2.5 77 | - zlib=1.2.12 78 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # PrimedRPA 2 | 3 | [![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](https://anaconda.org/bioconda/primedrpa) [![Anaconda-Server Badge](https://anaconda.org/bioconda/primedrpa/badges/license.svg)](https://anaconda.org/bioconda/primedrpa) [![Anaconda-Server Badge]( 4 | https://anaconda.org/bioconda/primedrpa/badges/latest_release_date.svg)](https://anaconda.org/bioconda/primedrpa) 5 | 6 | A python-based command-line package to augment primer and probe design for Recombinase Polymerase Amplification (RPA). 7 | 8 | 9 | ### Installation 10 | 11 | 12 | GitHub Installation 13 | 14 | ``` 15 | git clone https://github.com/MatthewHiggins2017/bioconda-PrimedRPA.git 16 | cd ./bioconda-PrimedRPA 17 | conda env create --file=PrimedRPA.yml 18 | conda activate RPA 19 | python setup.py install 20 | ``` 21 | 22 | Conda Installation 23 | 24 | ``` 25 | conda install -c bioconda primedrpa 26 | ``` 27 | 28 | 29 | ### Parameter Parsing 30 | 31 | Parameters can be parsed to PrimedRPA via the command line or using the PrimedRPA_Parameters.txt file. To download the text file 32 | please see the link below: 33 | 34 | ``` 35 | wget https://raw.githubusercontent.com/MatthewHiggins2017/bioconda-PrimedRPA/master/PrimedRPA_Parameters.txt 36 | ``` 37 | 38 | ### Key Output Files 39 | 40 | For each PrimedRPA run the following 3 key files are generated: 41 | 42 | ``` 43 | [RunID]_Alignment_Summary.csv 44 | [RunID]_Oligo_Binding_Sites.csv 45 | [RunID]_Output_Sets.csv 46 | ``` 47 | 48 | ### Walk-Through 49 | 50 | Please see the wiki for more information, including a step-by-step walk through of using the software. 51 | 52 | ### 3rd-Party Software 53 | 54 | PrimerRPA incorporates the following 3rd party software: 55 | 56 | Clustal Omega (http://www.clustal.org/omega/) - For sequence alignment if necessary.
57 | Blastn (https://blast.ncbi.nlm.nih.gov/Blast.cgi) - To assess primer/probe cross-reactivity.
58 | Samtools (http://www.htslib.org/) - To assess primer/probe cross-reactivity.
59 | 60 | 61 | 62 | ### Contact 63 | 64 | 65 | If you encounter any bugs please contact me directly at **matthew.higgins[at]lshtm.ac.uk** 66 | -------------------------------------------------------------------------------- /PrimedRPA_Parameters.txt: -------------------------------------------------------------------------------- 1 | This parameters file will guide the PrimedRPA-based primer and probe design process. Please follow the instructions outlined below: 2 | 3 | ----####---- 4 | Important Note - Do not remove any of the “>” and write your input directly after this symbol. 5 | ----####---- 6 | 7 | 8 | Please define the reference name for this PrimedRPA run: 9 | >Installation_Validation_Run 10 | 11 | Please indicate if you would like to use a previously generated Alignment File: [NO or File path] 12 | >NO 13 | 14 | Please indicate if you would like to use the previously generated Binding Sites: [NO or File path] 15 | >NO 16 | 17 | Please enter the path, from your current working directory, to the input fasta file: 18 | >Validation/Validation_1_Input.fasta 19 | 20 | Please classify the contents of the input fasta file as one of the following options: [SS, MS, AMS]. Whereby: 21 | SS = Single sequence 22 | MS = Multiple unaligned sequences 23 | MAS = Multiple aligned sequences 24 | 25 | >MS 26 | 27 | If multiple sequences are present in the input fasta file (Classification of MS or MAS), please indicate below the 28 | percentage identity required for the primers and probes target binding sites: 29 | >99 30 | 31 | Please indicate if a primer identity anchor is required. [NO or length of anchor] 32 | >NO 33 | 34 | Desired primer length (This can be a range: 28-32 or fixed value: 32): 35 | >28-32 36 | 37 | Please state if you require a probe to be designed and if so what type [NO,EXO,NFO] 38 | >NO 39 | 40 | Desired probe length (This can be a range: 45-50 or fixed value: 50): 41 | >50 42 | 43 | Below please define your max amplicon length. 44 | >300 45 | 46 | Below please state the repeat nucleotide cut-off in bp (e.g. 5bp will exclude sequences containing GGGGG). 47 | 48 | >5 49 | 50 | Below please insert the minimum percentage GC content for primer/probe: 51 | >40 52 | 53 | Below please insert the maximum percentage GC content for primer/probe: 54 | >60 55 | 56 | Below please indicate the percentage match tolerance for primer-probe dimerisation and secondary structure formation: 57 | >60 58 | 59 | Please enter [No or Path to Background file] below to identify if you want to perform a background DNA binding check: 60 | >Validation/Validation_1_Background.fasta 61 | 62 | Below please insert the percentage background cross reactivity threshold: 63 | >65 64 | 65 | Below please indicate if you would like to implement a Background Hard Fail Filter [NO,YES]: 66 | >NO 67 | 68 | Please define the maximum number of sets you would like to identify: 69 | >5 70 | 71 | Please define the number of threads available: 72 | >1 73 | 74 | Blastn Cross Reactivity Search Settings [Basic or Advanced or Fast] 75 | >Fast 76 | 77 | Blastn Evalue 78 | >1000 79 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /PrimedRPA: -------------------------------------------------------------------------------- 1 | #! /usr/bin/env python3 2 | 3 | ##################################################################### 4 | # PrimedRPA: RPA Primer and Probe Set Finder # 5 | # Higgins M et al. Submitted. 2018 # 6 | # # 7 | # Dependencies: # 8 | # Python 3.7 9 | # Glob 0.6 10 | # Pandas 0.20.3 # 11 | # Sys 3.6.3 # 12 | # Bio 1.70 # 13 | ##################################################################### 14 | 15 | 16 | # Install neccessary python libraries 17 | import os 18 | import sys 19 | import glob 20 | import subprocess 21 | import itertools 22 | import random 23 | import pandas as pd 24 | from collections import Counter 25 | from multiprocessing import Pool 26 | import argparse 27 | import re 28 | 29 | 30 | def FastaToDict(InputFile): 31 | fastadict = {} 32 | with open(InputFile) as file_one: 33 | for line in file_one: 34 | line = line.strip() 35 | if not line: 36 | continue 37 | if line.startswith(">"): 38 | active_sequence_name = line[1:] 39 | if active_sequence_name not in fastadict: 40 | fastadict[active_sequence_name] = '' 41 | continue 42 | sequence = line 43 | # If Uracil Present, Substitute for T (I.e. stick with 4 DNA bases) 44 | fastadict[active_sequence_name] += re.sub('U','T',sequence.upper()) 45 | return fastadict 46 | 47 | 48 | 49 | # Wrapper for clustal omega 50 | def RunningClustalo1(ClustalOPath, 51 | ListOfFileNames, 52 | overwriteOutput=True): 53 | 54 | print('Aligning Input File') 55 | for FileName in ListOfFileNames: 56 | OutputName = FileName.replace(".fasta",'_Aligned.fasta') 57 | command = "{0} -i {1} -o {2} --outfmt=fasta".format(ClustalOPath,FileName, OutputName) 58 | result = subprocess.call([command], stdout=subprocess.PIPE, shell=True,) 59 | 60 | 61 | # Function to generate reverse complement sequence 62 | def getComplement(seq, 63 | reverse=False, 64 | rule='N2N'): 65 | 66 | seqComp = "" 67 | for base in seq.upper(): 68 | base = base.upper() 69 | if base == "A": 70 | seqComp += "T" 71 | elif base == "T": 72 | seqComp += "A" 73 | elif base == "C": 74 | seqComp += "G" 75 | elif base == "G": 76 | seqComp += "C" 77 | elif base == 'U': 78 | seqComp += "A" 79 | elif base == "N": 80 | if rule == 'N2-': 81 | seqComp += '-' 82 | elif rule == 'N2N': 83 | seqComp += "N" 84 | elif base == "-": 85 | seqComp += "N" 86 | 87 | # If Character not any of above assign it as N 88 | else: 89 | seqComp += "N" 90 | 91 | if reverse: 92 | return(seqComp[::-1]) 93 | else: 94 | return(seqComp) 95 | 96 | 97 | 98 | ## Background Binding Check = TO IMPROVE 99 | def BlastnBackgroundCheck(seq,AllParameter): 100 | 101 | 102 | MaxBackgroundScoreBindingScore = 0 103 | MaxScoreBackSeq = '' 104 | HardFailBoolean = False 105 | 106 | RIS = str(random.randint(0,1000000)) 107 | 108 | 109 | #Create temp fasta file 110 | tempfastainput = open('./{}/{}_{}_Blastn_Input.fa'.format(AllParameter.PrimerBlastnOutput,seq,RIS),'w') 111 | tempfastainput.write('>Temp_Blastn_Fasta\n{}\n'.format(seq)) 112 | tempfastainput.close() 113 | 114 | 115 | # Parameters default for basic run 116 | Penalty = '-2' 117 | WordSize = '4' 118 | if AllParameter.BackgroundSearchSensitivity == 'Advanced': 119 | Penalty = '-1' 120 | 121 | elif AllParameter.BackgroundSearchSensitivity == 'Fast': 122 | Penalty = '-3' 123 | WordSize = '7' 124 | 125 | 126 | 127 | #Triggure Blastn command 128 | blastncommandrun = '{0} -word_size {5} -gapopen 5 -gapextend 2 -reward 1 -penalty {4} -evalue {7} -query {3}/{1}_{6}_Blastn_Input.fa -db {2}/{2} -out {3}/{1}_{6}_Blastn_Output.csv -outfmt "10 sseqid pident qstart qend sstart send evalue gaps sstrand" '.format(AllParameter.BlastnPath, 129 | seq, 130 | AllParameter.BlastnDBName, 131 | AllParameter.PrimerBlastnOutput, 132 | Penalty, 133 | WordSize, 134 | RIS, 135 | AllParameter.Evalue) 136 | 137 | 138 | 139 | subprocess.call([blastncommandrun],shell=True) 140 | 141 | # Remove Blastn Input File 142 | os.remove('./{}/{}_{}_Blastn_Input.fa'.format(AllParameter.PrimerBlastnOutput,seq,RIS)) 143 | 144 | # Try to read dataframe (may be empty if no alignments found) 145 | try: 146 | 147 | ShorterBackground = False 148 | 149 | blastnoutdf = pd.read_csv('{}/{}_{}_Blastn_Output.csv'.format(AllParameter.PrimerBlastnOutput,seq,RIS),header=None) 150 | blastnoutdf.columns=['Background_SeqID','Percentage Identity','qStart','qEnd','BackSeq_Start','BackSeq_End','Evalue','Number Of Gaps','Strand'] 151 | blastnoutdf['Cross Reactivity Score'] = ((((blastnoutdf['qEnd']+1) - blastnoutdf['qStart'])*(blastnoutdf['Percentage Identity']/100))/len(seq))*100 152 | blastnoutdf = blastnoutdf.sort_values(by=['Cross Reactivity Score'],ascending=False) 153 | 154 | 155 | for blastoutindex in blastnoutdf.index.tolist(): 156 | 157 | ReferenceID = blastnoutdf.loc[blastoutindex,'Background_SeqID'] 158 | if ReferenceID.count("|") == 2: 159 | CleanRefID = ReferenceID[ReferenceID.find("|")+1:-1] 160 | else: 161 | CleanRefID = ReferenceID 162 | 163 | # If Background Seq Is (+) Sense 164 | if blastnoutdf.loc[blastoutindex,'Strand']=='plus': 165 | 166 | UpperExtension = (len(seq)-blastnoutdf.loc[blastoutindex,'qEnd']) + blastnoutdf.loc[blastoutindex,'BackSeq_End'] 167 | LowerExtension = blastnoutdf.loc[blastoutindex,'BackSeq_Start'] - blastnoutdf.loc[blastoutindex,'qStart']+1 168 | 169 | if LowerExtension<0: 170 | LowerExtension = 0 171 | ShorterBackground = True 172 | 173 | SamToolsCommand = '{} faidx {} {}:{}-{} -o Adv_{}_{}_{}.fa'.format(AllParameter.SamtoolsPath, 174 | AllParameter.BackgroundCheck, 175 | CleanRefID, 176 | LowerExtension, 177 | UpperExtension, 178 | seq, 179 | CleanRefID, 180 | RIS) 181 | 182 | # If Background Seq Is (-) Sense 183 | else: 184 | UpperExtension = blastnoutdf.loc[blastoutindex,'BackSeq_Start'] + blastnoutdf.loc[blastoutindex,'qStart']-1 185 | LowerExtension = blastnoutdf.loc[blastoutindex,'BackSeq_End'] - (len(seq)-blastnoutdf.loc[blastoutindex,'qEnd']) 186 | 187 | 188 | if LowerExtension<0: 189 | LowerExtension = 0 190 | ShorterBackground = True 191 | 192 | SamToolsCommand = '{} faidx -i {} {}:{}-{} -o Adv_{}_{}_{}.fa'.format(AllParameter.SamtoolsPath, 193 | AllParameter.BackgroundCheck, 194 | CleanRefID, 195 | LowerExtension, 196 | UpperExtension, 197 | seq, 198 | CleanRefID, 199 | RIS) 200 | 201 | # Run Samtools Command 202 | subprocess.call([SamToolsCommand],shell=True,stdout=subprocess.DEVNULL,stderr=subprocess.DEVNULL) 203 | 204 | # Obtain Sequence 205 | fastadict = FastaToDict('Adv_{}_{}_{}.fa'.format(seq,CleanRefID,RIS)) 206 | 207 | # Extract Sequence & Complement 208 | ExtraSeq = list(fastadict.values())[0] 209 | ComplementSeq = getComplement(ExtraSeq) 210 | 211 | # Bug Fix 2020-07-06 - I.e. Only run if global alignment is complete 212 | if len(ComplementSeq) == len(seq): 213 | 214 | 215 | # Run SS Check Function 216 | BackgroundMaxBindingPercentage, BackgroundMaxBindingString, BackgroundHardFail, BackgroundString = SSIdentification(seq, ComplementSeq, False, ShorterBackground) 217 | 218 | # Add to Blastn DataFrame 219 | blastnoutdf.loc[blastoutindex,'Advanced Cross Reactivity Percentage'] = BackgroundMaxBindingPercentage 220 | blastnoutdf.loc[blastoutindex,'Advanced Cross Reactivity Percentage String'] = BackgroundMaxBindingString 221 | blastnoutdf.loc[blastoutindex,'Cross Reactivity Hard Fail'] = BackgroundHardFail 222 | blastnoutdf.loc[blastoutindex,'Cross Reactivity Hard Fail String'] = BackgroundString 223 | 224 | 225 | # Remove Advance Samtools Generated String 226 | os.remove('Adv_{}_{}_{}.fa'.format(seq,CleanRefID,RIS)) 227 | 228 | # Remove Raw Blastn Output 229 | os.remove('{}/{}_{}_Blastn_Output.csv'.format(AllParameter.PrimerBlastnOutput,seq,RIS)) 230 | 231 | # Save Clean Blast Output 232 | blastnoutdf = blastnoutdf.sort_values(by=['Advanced Cross Reactivity Percentage'],ascending=False) 233 | blastnoutdf.to_csv('{}/{}_Blastn_Output.csv'.format(AllParameter.PrimerBlastnOutput,seq),index=None) 234 | IndexOfInterest = blastnoutdf.index.tolist()[0] 235 | 236 | MaximumPercentageMatch = blastnoutdf.loc[IndexOfInterest,'Advanced Cross Reactivity Percentage'] 237 | MaxHomologyBackgroundSeq = blastnoutdf.iloc[IndexOfInterest,0] 238 | 239 | 240 | if True in blastnoutdf['Cross Reactivity Hard Fail'].unique(): 241 | HardFailBoolean = True 242 | 243 | 244 | # If dataframe empty e.g. no alignments at all 245 | except pd.errors.EmptyDataError: 246 | MaximumPercentageMatch = 0 247 | 248 | if MaximumPercentageMatch > MaxBackgroundScoreBindingScore: 249 | MaxBackgroundScoreBindingScore = MaximumPercentageMatch 250 | MaxScoreBackSeq = MaxHomologyBackgroundSeq 251 | 252 | 253 | return (MaxBackgroundScoreBindingScore, MaxScoreBackSeq, HardFailBoolean) 254 | 255 | 256 | # Creates Exo Fluorescent Probe 257 | def RunFluroProbeAnalysis(ProbeBindingSeq): 258 | 259 | minIndexPosition = int(len(ProbeBindingSeq)*0.45) 260 | maxIndexPosition = int(len(ProbeBindingSeq)*0.75) 261 | 262 | ProbeValidPass = False 263 | basenumber = 0 264 | proberegionlength = len(ProbeBindingSeq) 265 | for base in ProbeBindingSeq: 266 | if (basenumber + 4) < proberegionlength: 267 | basenumber += 1 268 | if minIndexPosition < basenumber < maxIndexPosition and base == "T": 269 | if (basenumber + 2) < proberegionlength: 270 | if ProbeBindingSeq[(basenumber+2)] == "T" or ProbeBindingSeq[(basenumber+3)] == "T": 271 | # State that probe seq passed in forward sense. 272 | ProbeValidPass = True 273 | # New Break For Loop 274 | break 275 | return ProbeValidPass 276 | 277 | 278 | # Secondary Structure Filter 279 | def SSIdentification(SeqOne, SeqTwo, ReverseOrientation, FixedBack=False ,threshold=4): 280 | 281 | # Nucleotide Dict 282 | NucDict = {'A':'T', 283 | 'T':'A', 284 | 'C':'G', 285 | 'G':'C', 286 | } 287 | 288 | # Maximum Binding sites 289 | MaxBindingSites = 0 290 | MaxBindingString = '' 291 | MaxBindingPercentage = 0 292 | 293 | # Hard Fail Sites 294 | MaxHardFailScore = 0 295 | HardFail = False 296 | HardFailString = '' 297 | 298 | # Max length of string according to shift. 299 | MaxLength = len(SeqOne) + len(SeqTwo) - 1 300 | 301 | # Add white space to end of sequences 302 | SeqOneNorm = SeqOne + ' '*(MaxLength-len(SeqOne)) 303 | SeqTwoNorm = SeqTwo + ' '*(MaxLength-len(SeqTwo)) 304 | SeqTwoReversed = SeqTwo[::-1] + ' '*(MaxLength-len(SeqTwo)) 305 | 306 | 307 | if ReverseOrientation == True: 308 | CombosToCheck = [(SeqTwoNorm,SeqOneNorm), 309 | (SeqOneNorm,SeqTwoNorm), 310 | (SeqOneNorm,SeqTwoReversed), 311 | (SeqTwoReversed,SeqOneNorm)] 312 | else: 313 | CombosToCheck = [(SeqTwoNorm,SeqOneNorm), 314 | (SeqOneNorm,SeqTwoNorm)] 315 | 316 | 317 | 318 | 319 | # Loop through var pairs whereby the first element will be shifted 320 | for VarPair in CombosToCheck: 321 | 322 | # Loop through possible shift positions 323 | for i in list(range(VarPair[0].count(' ')+1)): 324 | 325 | 326 | if i == 0: 327 | DynamicSeq = VarPair[0] 328 | else: 329 | DynamicSeq = ' '*i + VarPair[0][:-i] 330 | 331 | DyanimicSeqList = list(DynamicSeq) 332 | FixedSeqList = list(VarPair[1]) 333 | 334 | 335 | # This shall house the syntax to represent binding 336 | PossibleBindingString = '' 337 | 338 | for StringPos in list(range(len(DyanimicSeqList))): 339 | if DyanimicSeqList[StringPos] in list(NucDict.keys()): 340 | if NucDict[DyanimicSeqList[StringPos]] == FixedSeqList[StringPos]: 341 | PossibleBindingString += '|' 342 | else: 343 | PossibleBindingString += '-' 344 | else: 345 | PossibleBindingString += '-' 346 | 347 | NumberOfBindingMatches = PossibleBindingString.count('|') 348 | CompleteBindingString = DynamicSeq + '\n' + PossibleBindingString + '\n' + VarPair[1] 349 | 350 | 351 | # Fixed String 352 | if VarPair[1] == SeqOneNorm: 353 | FiveIndex = 0 354 | ThreeIndex = len(SeqOne) 355 | 356 | # Dyamic String 357 | else: 358 | FiveIndex = i 359 | ThreeIndex = i + len(SeqOne) 360 | 361 | 362 | UpperLimit = FiveIndex+22 363 | LowerLimit = ThreeIndex-22 364 | if LowerLimit <0: 365 | LowerLimit = 0 366 | 367 | 368 | # Determine 5 Prime Counts 369 | FivePrimeCounts = PossibleBindingString[FiveIndex:UpperLimit] 370 | 371 | # Determine 3 Prime Counts 372 | ThreePrimeCounts = PossibleBindingString[LowerLimit:ThreeIndex] 373 | 374 | 375 | weightings = [3,2,1.5] 376 | ThreePrimeLoc = [-1,-2,-3] 377 | FivePrimeLoc = [0,1,2] 378 | 379 | 380 | OriginalScore = [FivePrimeCounts,ThreePrimeCounts] 381 | IndexLocations = [FivePrimeLoc,ThreePrimeLoc] 382 | 383 | AdjustedWeights = [] 384 | for ib in [0,1]: 385 | TempScore = OriginalScore[ib].count('|') - OriginalScore[ib].count('-') 386 | Indexes = IndexLocations[ib] 387 | for iz in list(zip(Indexes,weightings)): 388 | if OriginalScore[ib][iz[0]] == '|': 389 | TempScore += iz[1] - 1 390 | AdjustedWeights.append(TempScore) 391 | 392 | if max(AdjustedWeights) >= 21.5: 393 | HardFail = True 394 | HardFailString = CompleteBindingString 395 | 396 | 397 | if MaxBindingSites < NumberOfBindingMatches: 398 | MaxBindingSites = NumberOfBindingMatches 399 | MaxBindingString = CompleteBindingString 400 | 401 | if FixedBack == False: 402 | Denom = min([len(SeqOne),len(SeqTwo)]) 403 | else: 404 | Denom = len(SeqOne) 405 | 406 | MaxBindingPercentage = (MaxBindingSites/Denom)*100 407 | 408 | return (MaxBindingPercentage,MaxBindingString, HardFail, HardFailString) 409 | 410 | 411 | 412 | 413 | 414 | # Creating Alignment DF Multithread Function 415 | def CreatingInputHomologyDF(fastadict,FastaIndexList): 416 | AlignedDF = pd.DataFrame() 417 | 418 | for seqindex in FastaIndexList: 419 | TempNucleotides = [] 420 | for faseq in fastadict.values(): 421 | TempNucleotides.append(faseq[seqindex]) 422 | 423 | # Remove NoN-specific Nucleotides = IUPAC designated the symbols for nucleotides 424 | TempNucleotides = [TN for TN in TempNucleotides if TN not in ['W','S','M', 425 | 'K','R','Y', 426 | 'N']] 427 | if (len(TempNucleotides) == 2 and 428 | '-' in TempNucleotides): 429 | MostCommonN = '-' 430 | NRepresentation = -100 #Harsh weighting against splits 431 | else: 432 | BugFix = Counter(TempNucleotides) 433 | MostCommonN = max(TempNucleotides, key=BugFix.get) 434 | if MostCommonN == '-': 435 | NRepresentation = -100 #Harsh weighting against splits 436 | else: 437 | NRepresentation = TempNucleotides.count(MostCommonN)/len(TempNucleotides) 438 | AlignedDF = AlignedDF.append({'Index_Pos':seqindex,'Nucleotide':MostCommonN,'IdentityScore':NRepresentation},ignore_index=True) 439 | 440 | 441 | return AlignedDF 442 | 443 | 444 | def IndentifyingAndFilteringOligos(AllParameter, 445 | AlignedDF, 446 | PossibleStartIndexes): 447 | 448 | 449 | OligoDF = pd.DataFrame() 450 | TargetSiteLengths = [AllParameter.PrimerLength] 451 | if AllParameter.ProbeRequired in ['EXO','NFO']: 452 | TargetSiteLengths.append(AllParameter.ProbeLength) 453 | 454 | # Loop through primer or probe 455 | for TSLP in TargetSiteLengths: 456 | if TSLP == AllParameter.PrimerLength: 457 | OligoType = 'Primer' 458 | else: 459 | OligoType = 'Probe' 460 | 461 | # Add in ability to handle specified range or primer or probe values. 462 | if '-' in str(TSLP): 463 | TSLRangePrior = [int(TSLI) for TSLI in TSLP.split('-')] 464 | TSLList = list(range(TSLRangePrior[0],TSLRangePrior[1]+1)) 465 | 466 | else: 467 | TSLList = [int(TSLP)] 468 | 469 | # Loop through possible oligo lengths. 470 | for TSL in TSLList: 471 | 472 | # Loop through possible start sites 473 | for i in PossibleStartIndexes: 474 | 475 | # Make Sure dont go too far out of dataframe 476 | if i+TSL=i)&(AlignedDF['Index_Pos']<=(i+TSL-1))] 479 | MeanHomologyScore = DFSubSet['IdentityScore'].mean() 480 | 481 | 482 | IDSList = DFSubSet['IdentityScore'].tolist() 483 | OutIDScore = [] 484 | for IDSO in [IDSList,IDSList[::-1]]: 485 | IDScore = 0 486 | for SCI in list(range(len(IDSO))): 487 | if float(IDSO[SCI]) == 1.0: 488 | IDScore +=1 489 | else: 490 | break 491 | OutIDScore.append(IDScore) 492 | 493 | 494 | ThreePrimeIdentityScore = OutIDScore[1] 495 | FivePrimerIdentityScore = OutIDScore[0] 496 | 497 | 498 | if MeanHomologyScore >= AllParameter.IdentityThreshold: 499 | NucleotideSeq = ''.join(DFSubSet['Nucleotide'].tolist()) 500 | NucleotideSeq = NucleotideSeq.upper() 501 | 502 | #Check Length of Oligo 503 | if len(NucleotideSeq) == TSL: 504 | 505 | # Assess GC Content 506 | GCPercentage = ((NucleotideSeq.count('G') + NucleotideSeq.count('C'))/len(NucleotideSeq))*100 507 | if (GCPercentage < AllParameter.MaxGC and GCPercentage > AllParameter.MinGC): 508 | 509 | # Assess Repeat Nucleotide 510 | NoRepeat = True 511 | for RROI in ['N','A','G','C','T']: 512 | RROIString = RROI * AllParameter.NucleotideRepeatLimit 513 | if RROIString in NucleotideSeq: 514 | NoRepeat = False 515 | 516 | if NoRepeat == True: 517 | 518 | # Run Secondary Structure Check / Self Dimerisation 519 | SDSSFilterPass=True 520 | MaxBindingSites, MaxBindingString, IgnoreThresh, IgnoreString = SSIdentification(NucleotideSeq,NucleotideSeq,True) 521 | if MaxBindingSites > AllParameter.DimerisationThresh: 522 | SDSSFilterPass=False 523 | 524 | 525 | if SDSSFilterPass == True: 526 | # Define row dictionary if passed all above stages 527 | RowDict = {'Oligo_Sequence':NucleotideSeq, 528 | 'Oligo_Type':OligoType, 529 | 'Binding_Site_Start_Index':i, 530 | 'Oligo_Length':TSL, 531 | 'Identity_Score':MeanHomologyScore, 532 | 'GC_Content': GCPercentage, 533 | 'Dimerisation Percentage Score':MaxBindingSites, 534 | 'Dimerisation String':MaxBindingString, 535 | '3 prime conserved identity':ThreePrimeIdentityScore, 536 | '5 prime conserved identity':FivePrimerIdentityScore} 537 | 538 | # Assess if Specific Probe Check is Needed. 539 | ProbePass = True 540 | if OligoType == 'Probe': 541 | 542 | # Run Specific Exo Probe Checks 543 | if AllParameter.ProbeRequired == 'EXO': 544 | ProbePass = RunFluroProbeAnalysis(NucleotideSeq) 545 | 546 | 547 | if ProbePass == True: 548 | 549 | # Add Run Blastn Check 550 | BlastnPass = True 551 | #If Background Check Neccessary Look To Change Blastn pass 552 | if AllParameter.BackgroundCheck.upper() != 'NO': 553 | 554 | # Run Blastn Check And If Passess Write Out Set 555 | MaxBackgroundScoreBindingScore, MaxScoreBackSeq, HardFailBool = BlastnBackgroundCheck(NucleotideSeq, AllParameter) 556 | 557 | 558 | # Check to see if Max Binding Score Less Than Threshold 559 | if MaxBackgroundScoreBindingScore > AllParameter.CrossReactivityThresh: 560 | BlastnPass = False 561 | 562 | 563 | else: 564 | RowDict['Max Background Cross Reactivity Score'] = MaxBackgroundScoreBindingScore 565 | RowDict['Max Background Cross Reactivity SeqID'] = MaxScoreBackSeq 566 | 567 | 568 | ## NEW NEW NEW ## - Check to see if oligo type is primer and then if it failed the hard-fail setting - Possible add parameter into this check as well 569 | if (HardFailBool == True and OligoType == 'Primer' and AllParameter.HardCrossReactFilter!='NO'): 570 | BlastnPass = False 571 | 572 | 573 | # If it passed Background Filtering 574 | if BlastnPass == True: 575 | OligoDF = OligoDF.append(RowDict,ignore_index=True) 576 | 577 | # Return Primer/Probe DataFrame 578 | return OligoDF 579 | 580 | 581 | def ComboIdentifyier(PrimerSS,ReversePrimerSS,ProbeSS,AllParameter,PassedOligos,FPrimerL,RPrimerL,ProbeL): 582 | 583 | PassedSetsDataFrame = pd.DataFrame() 584 | CombosList = [] 585 | 586 | for FP in PrimerSS: 587 | 588 | # If Probe Required 589 | if AllParameter.ProbeRequired in ['EXO','NFO']: 590 | Probes = [prss for prss in ProbeSS if (prss >= (FP+FPrimerL) and 591 | prss<= (FP+AllParameter.AmpliconSizeLimit-RPrimerL-ProbeL))] 592 | 593 | for Probe in Probes: 594 | ReversePrimers = [rpss for rpss in ReversePrimerSS if (rpss >= (Probe+ProbeL) and 595 | rpss <= (FP+AllParameter.AmpliconSizeLimit-RPrimerL))] 596 | 597 | CombosList += list(itertools.product([FP],ReversePrimers,[Probe])) 598 | 599 | # Probe Not Required 600 | else: 601 | ReversePrimers = [rpss for rpss in ReversePrimerSS if (rpss >= (FP+FPrimerL) and 602 | rpss <= (FP+AllParameter.AmpliconSizeLimit-RPrimerL))] 603 | 604 | CombosList += list(itertools.product([FP],ReversePrimers)) 605 | 606 | 607 | # Extract Valid Primer-Probe Combos 608 | for Combo in CombosList: 609 | # Identify Indexes 610 | FPIndex = PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['Oligo_Length']==FPrimerL)&(PassedOligos['Binding_Site_Start_Index']==Combo[0])].index.tolist()[0] 611 | RPIndex = PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['Oligo_Length']==RPrimerL)&(PassedOligos['Binding_Site_Start_Index']==Combo[1])].index.tolist()[0] 612 | 613 | 614 | # Extract Combo Primer Sequences - (Reverse Complement RP) 615 | ComboSeqList = [PassedOligos.loc[FPIndex,'Oligo_Sequence'],getComplement(PassedOligos.loc[RPIndex,'Oligo_Sequence'],True)] 616 | 617 | # Add Probe Sequence If Necessary 618 | if AllParameter.ProbeRequired in ['EXO','NFO']: 619 | ProbeIndex = PassedOligos[(PassedOligos['Oligo_Type']=='Probe')&(PassedOligos['Oligo_Length']==ProbeL)&(PassedOligos['Binding_Site_Start_Index']==Combo[2])].index.tolist()[0] 620 | ComboSeqList.append(PassedOligos.loc[ProbeIndex,'Oligo_Sequence']) 621 | 622 | 623 | #Run Dimerisation Check And If Passess Continue 624 | DimerisationPass = True 625 | MaxComboSSScore = 0 626 | MaxComboSSString = '' 627 | for SSSCombo in list(itertools.combinations(ComboSeqList,r=2)): 628 | SSMaxBindingSites, SSMaxBindingString, IgnoreThresh, IgnoreString = SSIdentification(SSSCombo[0],SSSCombo[1],True) 629 | 630 | if SSMaxBindingSites > MaxComboSSScore: 631 | MaxComboSSScore = SSMaxBindingSites 632 | MaxComboSSString = SSMaxBindingString 633 | 634 | 635 | if MaxComboSSScore > AllParameter.DimerisationThresh: 636 | DimerisationPass = False 637 | 638 | if DimerisationPass == True: 639 | 640 | BlastnPass = True ### REMOVE INDEX AT LATER DATE 641 | 642 | 643 | # Add Everything To DF If Passed All Parameters 644 | if BlastnPass == True: 645 | 646 | PassedComboRow = {'Forward Primer (FP)':ComboSeqList[0], 647 | 'FP GC%': PassedOligos.loc[FPIndex,'GC_Content'], 648 | 'FP Binding Start Site': PassedOligos.loc[FPIndex,'Binding_Site_Start_Index'], 649 | 'Reverse Primer (RP)': ComboSeqList[1], 650 | 'RP GC%': PassedOligos.loc[RPIndex,'GC_Content'], 651 | 'RP Binding Start Site': PassedOligos.loc[RPIndex,'Binding_Site_Start_Index'], 652 | 'Amplicon Size': PassedOligos.loc[RPIndex,'Binding_Site_Start_Index'] + RPrimerL - PassedOligos.loc[FPIndex,'Binding_Site_Start_Index'], 653 | 'Max Dimerisation Percentage Score':SSMaxBindingSites, 654 | 'Max Dimerisation String':MaxComboSSString, 655 | 'Forward Primer Length':FPrimerL, 656 | 'Reverse Primer Length':RPrimerL, 657 | "Minimum Primer 3' Identity Anchor": min([PassedOligos.loc[RPIndex,'5 prime conserved identity'], PassedOligos.loc[FPIndex,'3 prime conserved identity']]) 658 | } 659 | 660 | MaxBackgroundScoresIndexes = [FPIndex,RPIndex] 661 | 662 | if AllParameter.ProbeRequired in ['EXO','NFO']: 663 | PassedComboRow['Probe (P)'] = ComboSeqList[2] 664 | PassedComboRow['Probe GC%'] = PassedOligos.loc[ProbeIndex,'GC_Content'] 665 | PassedComboRow['Probe Binding Start Site'] = PassedOligos.loc[ProbeIndex,'Binding_Site_Start_Index'] 666 | PassedComboRow['Probe Length'] = ProbeL 667 | MaxBackgroundScoresIndexes.append(ProbeIndex) 668 | 669 | 670 | if AllParameter.BackgroundCheck != 'NO': 671 | 672 | MaxBackgroundScoreBindingScore = 0 673 | MaxScoreBackSeq = '' 674 | for SucIndex in MaxBackgroundScoresIndexes: 675 | if PassedOligos.loc[SucIndex,'Max Background Cross Reactivity Score'] > MaxBackgroundScoreBindingScore: 676 | MaxBackgroundScoreBindingScore = PassedOligos.loc[SucIndex,'Max Background Cross Reactivity Score'] 677 | MaxScoreBackSeq = PassedOligos.loc[SucIndex,'Max Background Cross Reactivity SeqID'] 678 | 679 | 680 | PassedComboRow['Max Background Cross Reactivity Score'] = MaxBackgroundScoreBindingScore 681 | PassedComboRow['Max Background Binding Seq'] = MaxScoreBackSeq 682 | 683 | 684 | # Add Passed Row To DataFrame 685 | PassedSetsDataFrame = PassedSetsDataFrame.append(PassedComboRow,ignore_index=True) 686 | 687 | return PassedSetsDataFrame 688 | 689 | # Main Function To Generate Primer - Probe Combos 690 | def CheckingAlignedOutputFile(AllParameter): 691 | 692 | 693 | # Check If Binding Sites Already Exist 694 | if AllParameter.PriorBindingSite != 'NO': 695 | 696 | print('Reading In Oligo Binding Sites') 697 | 698 | PassedOligos = pd.read_csv('{}'.format(AllParameter.PriorBindingSite)) 699 | 700 | 701 | # Filter on Parameters Passed In 702 | PassedOligos = PassedOligos[(PassedOligos['GC_Content']>=AllParameter.MinGC)& 703 | (PassedOligos['GC_Content']<=AllParameter.MaxGC)& 704 | (PassedOligos['Dimerisation Percentage Score']<=AllParameter.DimerisationThresh)& 705 | (PassedOligos['Identity_Score']>=AllParameter.IdentityThreshold)] 706 | 707 | 708 | # Filter on Primer + Probe Ranges - (Tidy Up At Later Date) 709 | PPLengthDict = {} 710 | PrimerRange=False 711 | ProbeRange = False 712 | for LL in [AllParameter.PrimerLength,AllParameter.ProbeLength]: 713 | if LL == AllParameter.PrimerLength: 714 | LLType = 'Primer' 715 | else: 716 | LLType = 'Probe' 717 | 718 | if '-' in str(LL): 719 | LLRangePrior = [int(LLLI.strip()) for LLLI in LL.split('-')] 720 | PPLengthDict['{}_Max'.format(LLType)] = max(LLRangePrior) 721 | PPLengthDict['{}_Min'.format(LLType)] = min(LLRangePrior) 722 | if LLType == 'Primer': 723 | PrimerRange = True 724 | else: 725 | ProbeRange = True 726 | else: 727 | PPLengthDict['{}_Len'.format(LLType)] = int(LL) 728 | 729 | 730 | if PrimerRange == True: 731 | PrimerPassedSubet = PassedOligos[(PassedOligos['Oligo_Type']=='Primer') & 732 | (PassedOligos['Oligo_Length']>=PPLengthDict['Primer_Min']) & 733 | (PassedOligos['Oligo_Length']<=PPLengthDict['Primer_Max']) ] 734 | else: 735 | PrimerPassedSubet = PassedOligos[(PassedOligos['Oligo_Type']=='Primer') & 736 | (PassedOligos['Oligo_Length']==PPLengthDict['Primer_Len'])] 737 | 738 | 739 | if ProbeRange == True: 740 | ProbePassedSubet = PassedOligos[(PassedOligos['Oligo_Type']=='Probe') & 741 | (PassedOligos['Oligo_Length']>=PPLengthDict['Probe_Min']) & 742 | (PassedOligos['Oligo_Length']<=PPLengthDict['Probe_Max']) ] 743 | 744 | 745 | else: 746 | ProbePassedSubet = PassedOligos[(PassedOligos['Oligo_Type']=='Probe') & 747 | (PassedOligos['Oligo_Length']==PPLengthDict['Probe_Len'])] 748 | 749 | 750 | PassedOligos = pd.concat([PrimerPassedSubet,ProbePassedSubet]).reset_index().drop(['index'],axis=1) 751 | 752 | 753 | # If Background Check is Present filter 754 | if AllParameter.BackgroundCheck != 'NO': 755 | PassedOligos = PassedOligos[PassedOligos['Max Background Cross Reactivity Score']<=AllParameter.CrossReactivityThresh] 756 | 757 | 758 | ##Check If No Primers Passed Subset 759 | if len(PrimerPassedSubet)==0: 760 | print('No Oligos Passed Filtering') 761 | sys.exit() 762 | 763 | if AllParameter.ProbeRequired!='NO': 764 | if len(ProbePassedSubet)==0: 765 | print('No Oligos Passed Filtering') 766 | sys.exit() 767 | 768 | 769 | #Create Binding DataFrame If It Doesnt Exist 770 | else: 771 | 772 | # Load In User Specified 773 | if AllParameter.PriorAlign != 'NO': 774 | print('Reading Alignment Summary') 775 | MergedAlignedDF = pd.read_csv('{}'.format(AllParameter.PriorAlign)) 776 | HDFLST = list(range(len(MergedAlignedDF))) 777 | HomoDFInputIndexBlocks = [HDFLST[i:i + AllParameter.Threads] for i in range(0, len(HDFLST), AllParameter.Threads)] 778 | 779 | 780 | # Create Alignment DF if it doesnt exist 781 | else: 782 | print('Generating Alignment Summary') 783 | 784 | 785 | # Read in the aligned fasta sequences 786 | fastadict = FastaToDict(AllParameter.InputFile) 787 | 788 | # Extract Alignment Length and QC 789 | FirstSeq = True 790 | FastaSeqLength = 0 791 | for fastaseq in fastadict.values(): 792 | if FirstSeq == True: 793 | FastaSeqLength = len(fastaseq) 794 | FirstSeq = False 795 | if len(fastaseq) != FastaSeqLength: 796 | sys.exit('ERROR: Alignment file error length of all sequences is not equal') 797 | 798 | 799 | # Generate Neccessary Alignment Summary DF 800 | HDFLST = list(range(FastaSeqLength)) 801 | HomoDFInputIndexBlocks = [HDFLST[i:i + AllParameter.Threads] for i in range(0, len(HDFLST), AllParameter.Threads)] 802 | MTDFOVI = list(zip([fastadict]*len(HomoDFInputIndexBlocks),HomoDFInputIndexBlocks)) 803 | 804 | 805 | with Pool(processes=AllParameter.Threads) as pool: 806 | AlignedDFMultiThreadOupt = pool.starmap(CreatingInputHomologyDF,MTDFOVI) 807 | MergedAlignedDF = pd.concat(AlignedDFMultiThreadOupt).reset_index().drop(['index'],axis=1) 808 | MergedAlignedDF = MergedAlignedDF.sort_values(by=['Index_Pos']) 809 | MergedAlignedDF.to_csv('{}_Alignment_Summary.csv'.format(AllParameter.RunID),index=None) 810 | 811 | 812 | print('Generating Primer/Probe Binding Site DataFrame') 813 | # Generating Primer/Probe Binding Site DataFrame 814 | PrimerProbeCheckParallelInput = list(zip([AllParameter]*len(HomoDFInputIndexBlocks), 815 | [MergedAlignedDF]*len(HomoDFInputIndexBlocks), 816 | HomoDFInputIndexBlocks)) 817 | 818 | with Pool(processes=AllParameter.Threads) as pool: 819 | PotentialPrimerProbeOut = pool.starmap(IndentifyingAndFilteringOligos,PrimerProbeCheckParallelInput) 820 | 821 | 822 | PassedOligos = pd.concat(PotentialPrimerProbeOut).reset_index().drop(['index'],axis=1) 823 | if len(PassedOligos) == 0: 824 | print('No Oligos Passed Filtering') 825 | sys.exit() 826 | PassedOligos.to_csv('{}_PrimedRPA_Oligo_Binding_Sites.csv'.format(AllParameter.RunID),index=None) 827 | 828 | 829 | 830 | # Identify Primer-Probe Sets 831 | print('Identifying Valid Primer-Probe Combinations') 832 | FinalOutputDF = pd.DataFrame() 833 | 834 | # Determine all probe lengths available 835 | if AllParameter.ProbeRequired in ['EXO','NFO']: 836 | PossibleProbeLengths = PassedOligos[PassedOligos['Oligo_Type']=='Probe'].loc[:,'Oligo_Length'].unique().tolist() 837 | 838 | else: 839 | PossibleProbeLengths = [0] 840 | 841 | # Loop through possible FP lengths 842 | if AllParameter.ConservedAnchor == 'NO': 843 | AllParameter.ConservedAnchor = 0 844 | else: 845 | AllParameter.ConservedAnchor = int(AllParameter.ConservedAnchor) 846 | 847 | 848 | # Loop though Starting Forward Length 849 | for SFPL in PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['3 prime conserved identity']>=AllParameter.ConservedAnchor)].loc[:,'Oligo_Length'].unique(): 850 | 851 | # Identify all possible FP starting sites 852 | PossibleForwardPrimerSS = PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['Oligo_Length']==SFPL)&(PassedOligos['3 prime conserved identity']>=AllParameter.ConservedAnchor)].loc[:,'Binding_Site_Start_Index'].tolist() 853 | 854 | # Loop through all possible RP lengths 855 | for SRPL in PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['5 prime conserved identity']>=AllParameter.ConservedAnchor)].loc[:,'Oligo_Length'].unique(): 856 | 857 | # Identify all possible RP starting sites 858 | PossibleReversePrimerSS = PassedOligos[(PassedOligos['Oligo_Type']=='Primer')&(PassedOligos['Oligo_Length']==SRPL)&(PassedOligos['5 prime conserved identity']>=AllParameter.ConservedAnchor)].loc[:,'Binding_Site_Start_Index'].tolist() 859 | 860 | # Split FP sites into tranches based on number of threads available. 861 | random.shuffle(PossibleForwardPrimerSS) 862 | PrimerStartSiteTranchesOne = [PossibleForwardPrimerSS[i:i + 2] for i in range(0, len(PossibleForwardPrimerSS), 2)] 863 | PrimerStartSiteTranchesTwo = [PrimerStartSiteTranchesOne[i:i + AllParameter.Threads] for i in range(0, len(PrimerStartSiteTranchesOne), AllParameter.Threads)] 864 | 865 | # Loop through possible probe lengths. 866 | for PPL in PossibleProbeLengths: 867 | 868 | if PPL == 0: 869 | PossibleProbeSS = [] 870 | 871 | else: 872 | PossibleProbeSS = PassedOligos[(PassedOligos['Oligo_Type']=='Probe')&(PassedOligos['Oligo_Length']==PPL)].loc[:,'Binding_Site_Start_Index'].tolist() 873 | 874 | for PSST in PrimerStartSiteTranchesTwo: 875 | if len(FinalOutputDF) < AllParameter.MaxSets: ## Check this threshold setting. 876 | ComboSearchInput = list(zip(PSST, 877 | [PossibleReversePrimerSS]*len(PSST), 878 | [PossibleProbeSS]*len(PSST), 879 | [AllParameter]*len(PSST), 880 | [PassedOligos]*len(PSST), 881 | [SFPL]*len(PSST), 882 | [SRPL]*len(PSST), 883 | [PPL]*len(PSST))) 884 | 885 | 886 | 887 | with Pool(processes=AllParameter.Threads) as pool: 888 | SuccessfulSets = pool.starmap(ComboIdentifyier,ComboSearchInput) 889 | 890 | TempOutputDF = pd.concat(SuccessfulSets) 891 | FinalOutputDF = pd.concat([FinalOutputDF,TempOutputDF]) 892 | if len(FinalOutputDF) != 0: 893 | FinalOutputDF.to_csv('{}_Output_Sets.csv'.format(AllParameter.RunID),index=None) 894 | 895 | 896 | print('PrimedRPA Complete') 897 | print('If helpful, please cite:\n\nHiggins M et al. Submitted. 2018\nDOI: 10.1093/bioinformatics/bty701') 898 | 899 | 900 | ######################################################################################################################## 901 | ######################################################################################################################## 902 | ######################################################################################################################## 903 | 904 | 905 | print('\n\n') 906 | print('-------------------------------------------') 907 | print('----------------PrimedRPA------------------') 908 | print('-----Finding RPA Primer and Probe Sets-----') 909 | print('-------------Higgins M et al.--------------') 910 | print('-------------------------------------------\n\n') 911 | 912 | 913 | 914 | try: 915 | # Utilise Either Parameters File Or Command Line Interface 916 | if 'PrimedRPA_Parameters.txt' in sys.argv[1]: 917 | 918 | # Import and Extract Parameters 919 | parametersFile = sys.argv[1] 920 | try: 921 | paraFile = open(parametersFile,"r") 922 | iu = [] 923 | for line in paraFile.readlines(): 924 | if ">" in line: 925 | n = line.strip('\n') 926 | h = n.strip('>') 927 | iu.append(h) 928 | u = iu[1:] 929 | 930 | class AllParameter: 931 | RunID = str(u[0]) 932 | PriorAlign = str(u[1]) 933 | PriorBindingSite = str(u[2]) 934 | InputFile = str(u[3]) 935 | InputFileType = str(u[4]) 936 | IdentityThreshold = int(u[5])/100 937 | ConservedAnchor = str(u[6]).strip() 938 | PrimerLength = u[7].strip() 939 | ProbeRequired = str(u[8]).upper() 940 | ProbeLength = u[9].strip() 941 | AmpliconSizeLimit = int(u[10]) 942 | NucleotideRepeatLimit = int(u[11]) 943 | MinGC = int(u[12]) 944 | MaxGC = int(u[13]) 945 | DimerisationThresh = int(u[14]) 946 | BackgroundCheck = str(u[15]) 947 | CrossReactivityThresh = int(u[16]) 948 | HardCrossReactFilter = str(u[17]) 949 | MaxSets = int(u[18]) 950 | Threads = int(u[19]) 951 | BackgroundSearchSensitivity = str(u[20]) 952 | Evalue=int(u[21]) 953 | 954 | 955 | except: 956 | print('Parameters File Could Not Be Opened\nCheck File Path.') 957 | sys.exit() 958 | 959 | else: 960 | 961 | parser = argparse.ArgumentParser() 962 | parser.add_argument('--RunID', help='Desired Run ID', required=True) 963 | parser.add_argument('--PriorAlign', help='Optional: Path to Prior Binding File',default='NO') 964 | parser.add_argument('--PriorBindingSite', help='Optional: Path to Prior Binding File',default='NO') 965 | parser.add_argument('--InputFile', help='Path to Input File',default='NO') 966 | parser.add_argument('--InputFileType', help='Options [SS,MS,MAS]') 967 | parser.add_argument('--IdentityThreshold', help='Desired Identity Threshold',default=0.99) 968 | parser.add_argument('--ConservedAnchor', help='Identity Anchor Required',type=str,default='NO') 969 | parser.add_argument('--PrimerLength', help='Desired Primer Length',type=str,default='30') 970 | parser.add_argument('--ProbeRequired', help='Options [NO,EXO,NFO]',type=str,default='NO') 971 | parser.add_argument('--ProbeLength', help='Desired Probe Length',type=str,default='50') 972 | parser.add_argument('--AmpliconSizeLimit', help='Amplicon Size Limit',type=int,default=500) 973 | parser.add_argument('--NucleotideRepeatLimit', help='Nucleotide Repeat Limit (i.e 5 = AAAAA)',type=int,default=5) 974 | parser.add_argument('--MinGC', help='Minimum GC Content',type=int,default=30) 975 | parser.add_argument('--MaxGC', help='Maximum GC Content',type=int,default=70) 976 | parser.add_argument('--DimerisationThresh', help='Percentage Dimerisation Tolerated',type=int,default=40) 977 | parser.add_argument('--BackgroundCheck', help='Options [NO, Path To Background Fasta File]',default='NO') 978 | parser.add_argument('--CrossReactivityThresh', help='Max Cross Reactivity Threshold',type=int,default=60) 979 | parser.add_argument('--HardCrossReactFilter', help='Hard Cross Reactivity Filter',type=str,default='NO') 980 | parser.add_argument('--MaxSets', help='Default Set To 100',type=int,default=100) 981 | parser.add_argument('--Threads', help='Default Set To 1',type=int,default=1) 982 | parser.add_argument('--BackgroundSearchSensitivity', help='Options [Basic or Advanced or Fast]',type=str,default='Basic') 983 | parser.add_argument('--Evalue', help='Default Set To 1000',type=int,default=1000) 984 | 985 | AllParameter = parser.parse_args() 986 | 987 | 988 | except: 989 | print('Please run PrimedRPA --help to see valid options') 990 | sys.exit() 991 | 992 | 993 | # Check Files Defined Exist 994 | FileLocationsCheckList = [AllParameter.PriorAlign, 995 | AllParameter.PriorBindingSite, 996 | AllParameter.BackgroundCheck, 997 | AllParameter.InputFile] 998 | 999 | for FL in FileLocationsCheckList: 1000 | if (FL != 'NO' and FL != ''): 1001 | if FL not in glob.glob(FL): 1002 | print('File Not Found: {}'.format(FL)) 1003 | sys.exit() 1004 | 1005 | 1006 | 1007 | #Define tool dependancy paths 1008 | AllParameter.BlastnPath = 'blastn' 1009 | AllParameter.BlastnDBCreationPath = 'makeblastdb' 1010 | AllParameter.ClustalOPath = 'clustalo' 1011 | AllParameter.SamtoolsPath = 'samtools' 1012 | 1013 | 1014 | # Create Blastn Database if neccessary 1015 | if AllParameter.BackgroundCheck.upper() != 'NO': 1016 | 1017 | AllParameter.BlastnDBName = '{}_Blastn_DB_PrimedRPA'.format(AllParameter.BackgroundCheck.split('/')[-1].split('.')[0]) 1018 | if os.path.exists(AllParameter.BlastnDBName) == False: 1019 | os.makedirs(AllParameter.BlastnDBName) 1020 | makeblastdbcommand = '{0} -in {1} -dbtype nucl -parse_seqids -out {2}/{2}'.format(AllParameter.BlastnDBCreationPath, 1021 | AllParameter.BackgroundCheck, 1022 | AllParameter.BlastnDBName) 1023 | 1024 | print('\nCreating Blastn Database:') 1025 | subprocess.call([makeblastdbcommand],shell=True) 1026 | print('\n') 1027 | 1028 | # Create directory to house blastn outputs 1029 | AllParameter.PrimerBlastnOutput = '{}/{}'.format(AllParameter.BlastnDBName,AllParameter.RunID) 1030 | if os.path.exists(AllParameter.PrimerBlastnOutput) == False: 1031 | os.mkdir(AllParameter.PrimerBlastnOutput) 1032 | 1033 | 1034 | # Check If Alignment Is Necessary 1035 | if (AllParameter.InputFileType == 'MS' and AllParameter.InputFile != 'NO') : 1036 | 1037 | # Check if MS Alignment already Exists in Working Directory 1038 | if AllParameter.InputFile.replace('.fasta','_Aligned.fasta') not in glob.glob(AllParameter.InputFile.replace('.fasta','_Aligned.fasta')): 1039 | RunningClustalo1(AllParameter.ClustalOPath,[AllParameter.InputFile], overwriteOutput=False) 1040 | 1041 | AllParameter.InputFile = AllParameter.InputFile.replace('.fasta','_Aligned.fasta') 1042 | 1043 | 1044 | # Run Primer, Probe Design process 1045 | if __name__ == '__main__': 1046 | CheckingAlignedOutputFile(AllParameter) 1047 | --------------------------------------------------------------------------------