├── LICENSE ├── README.md ├── docs ├── Fig4_draw1.png └── environment.yml └── scripts ├── Chapter_3_1.ipynb ├── Chapter_3_2.ipynb ├── Chapter_3_3.ipynb ├── Chapter_3_4.ipynb ├── Chapter_3_5.ipynb ├── Chapter_3_6.ipynb └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 Jan Zrimec 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 | ## Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure 2 | Link to paper: [10.1038/s41467-020-19921-4](https://doi.org/10.1038/s41467-020-19921-4) 3 | 4 | drawing 5 | Figure. Illustration of four genes (CDC6, RIO2, NSP1, EXG1) that carry a group of motif co-occurrence rules with a common motif (NHP6B transcription factor binding site, blue line) in their promoter region. The genes diverge in possessing 2 to 4 other DNA motifs (red lines) across the remaining regulatory regions (promoter, 5' and 3' UTRs and terminator), which repurpose the expression of these genes across a range of almost 3 orders of magnitude of expression levels. Red lines in the histogram denote the specific expression levels of the genes. 6 | 7 | --------------- 8 | This repository contains scripts to reproduce the analysis and figures. The data is available at [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3905252.svg)](https://doi.org/10.5281/zenodo.3905252), extract the archive to a folder named 'data'. 9 | 10 | Dependencies are provided in the conda environment.yml file in the 'docs' folder. 11 | -------------------------------------------------------------------------------- /docs/Fig4_draw1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JanZrimec/DeepExpression/c8cf61a14128c72235c11f0cd7fb6810bb5ad7f6/docs/Fig4_draw1.png -------------------------------------------------------------------------------- /docs/environment.yml: -------------------------------------------------------------------------------- 1 | name: py36_deepexp 2 | channels: 3 | - bioconda/label/cf201901 4 | - conda-forge 5 | - bioconda 6 | - anaconda 7 | - defaults 8 | dependencies: 9 | - biopython=1.73=py36h7b6447c_0 10 | - ipykernel=5.1.0=py36h39e3cac_0 11 | - logomaker=0.8=py_0 12 | - matplotlib=3.0.3=py36h5429711_0 13 | - numpy-base=1.16.2=py36hde5b4d6_0 14 | - pandas=0.25.3 15 | - pip=18.1=py36_0 16 | - python=3.6.7=h0371630_0 17 | - python-levenshtein=0.12.0=py36h516909a_1001 18 | - python-wget=3.2=py36_0 19 | - scikit-bio=0.5.2=py36h3010b51_0 20 | - scikit-learn=0.20.3=py36hd81dba3_0 21 | - seaborn=0.9.0=py36_0 22 | - statsmodels=0.9.0=py36h3010b51_1000 23 | - xlrd=1.2.0=py36_0 24 | - yaml=0.1.7=had09818_2 25 | - pip: 26 | - cairosvg==2.4.2 27 | - h5py==2.8.0 28 | - hyperopt==0.1.1 29 | - keras==2.2.4 30 | - keras-applications==1.0.6 31 | - keras-preprocessing==1.0.5 32 | - networkx==2.2 33 | - numpy==1.15.4 34 | - scipy==1.1.0 35 | - tensorboard==1.11.0 36 | - tensorflow==1.11.0 37 | - upsetplot==0.3.0 38 | prefix: /home/zrimec/miniconda3/envs/py36 39 | 40 | -------------------------------------------------------------------------------- /scripts/README.md: -------------------------------------------------------------------------------- 1 | Scripts to reproduce the figures and reported values in the paper. 2 | 3 | The model training and hyperparameter tuning pipeline can be found [here](https://github.com/zelezniak-lab/param_pipeline) albeit without documentation or usage instructions. 4 | --------------------------------------------------------------------------------