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JARVIS ("Junk" Annotation genome-wide Residual Variation Intolerance Score): a comprehensive deep learning framework to prioritise non-coding variants in whole genomes, using human-lineage purifying selection features and primary sequence context.
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gwRVIS (genome-wide Residual Variation Intolerance Score): genome-wide intolerance to variation score
| Publication: |
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| Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning. |
| Vitsios et al., Nature Communications, March 8, 2021 https://doi.org/10.1038/s41467-021-21790-4 |
- Python dependencies
conda create -n jarvis python=3.7 r r-devtools r-tidyverse
conda config --add channels bioconda
conda config --add channels conda-forge
conda activate jarvis
conda install --file requirements.txt
- R dependencies
install.packages(c("glm2", "glmnet", "lmridge", "plotmo", "pRoc", "ggplot2", "ggridges", "RColorBrewer")) devtools::install_github("thomasp85/patchwork")
- Instructions to generate the JARVIS and gwRVIS scores are available in the README.md file within
modules. - Subsequent sub-folders may also contain their own README files with instructions to run them independently or for ad-hoc analyses.
- Other folders and their sub-folders (such as
ensembl/,gnomad/andother_datasets/) are accompanied with README files and scripts to download and pre-process any other required datafiles that are not available in the JARVIS GitHub repositoy.
JARVIS and gwRVIS scores, across the whole genome, are publicly available at the following location: http://jarvis.public.cgr.astrazeneca.com
All scores have been generated based on the hg19 human assembly version.