ghfc-utils 0.0.9

Various tools and scripts used in the GHFC lab

ghfc-utils

set of small tools designed to help automatize simple task locally or on Pasteur's cluster.

• ghfc-reannotate for the postprocessing of slivar files including filtering and geneset reannotation.

Installation

pip install ghfc-utils

PS. on maestro, do not forget to load Python first (not needed anymore once installed):

module load Python/3.9.16

slivar reannotator

A tool to filter and reannotate slivar files according to various parameters and genesets. The goal is to produce a more generic kind of slivar files and to use this for the user to run their own filtering. ghfc-reannotate reads a slivar file and given a config file, will return an annotated and filtered slivar file.

usage: ghfc-reannotate [-h] [-c CHUNKSIZE] [-k] [-p] [-v] configuration slivar output

A tool to filter and reannotate slivar files according to various parameters and genesets.

positional arguments:
  configuration         config file
  slivar                slivar file to reannotate
  output                annotated slivar file

optional arguments:
  -h, --help            show this help message and exit
  -c CHUNKSIZE, --chunksize CHUNKSIZE
                        size of the chunks read from the input (default 100000)
  -k, --keep-all-transcripts
                        to keep all impacted transcript instead of the first
  -p, --progress        display a progress bar
  -v, --verbose         activate verbose mode

Example

You need to prepare a config file or take the one provided here. Then, you need a slivar file to run the tool on. For instance you can use the 570MB file at /pasteur/zeus/projets/p02/ghfc_wgs_zeus/WGS/Paris-AIMS2/slivar/Paris-AIMS2.slivar-full.lof_miss.tsv on zeus.

ghfc-reannotate config.yaml input_slivar.tsv output_slivar.tsv

The provided config file has a lot of comments to help build a new one.

how is it working?

• This tools read the slivar file before decomposing the impacts by transcripts (so 1 line per trancsript).
  • as slivar files can be really large in some project, the reading is done by chunks of 100k rows.
• Then filters on samples if required
• Then, it filters all lines using, in this order following the config file parameters:
  1. the geneset (based on the ENSG, mind the GRCh37/GRCh38 differences in ENSG)
  2. the impact / impact-categories
  3. if missense are kept, filtering them on their impact (using scores such as the mpc or the cadd)
  4. the gnomad frequency
  5. the pext
  6. LCR
• the variant/transcript are then sorted according to criteria given by the user in the config file from the most important to the least important
• for each sample, variant and gene (ENSG) the first transcript (most important given by the config criteria) is kept unless the --keep-all-transcripts option is used.

pext file

The pext is a bed file with the following columns (order important, there must be some header):

chr	start	end	max_brain	ensg	symbol

Need to have the genome version to match the data (GRCh37/38 and using the chr or not in the chromosome names)