WGS-based GBA variant caller
Project description
Gauchian: WGS-based GBA variant caller
Gauchian is a targeted variant caller for the GBA gene based on a whole-genome sequencing (WGS) BAM file. Gauchian uses a novel method to solve the problems caused by the high sequence similarity with the pseudogene paralog GBAP1 and is able to detect variants accurately in the Exons 9-11 homology region, such as large deletions or duplications between GBA and GBAP1, and GBAP1-like variants in GBA, including p.A495P, p.L483P, p.D448H, c.1263del, RecNciI, RecTL and c.1263del+RecTL. In addition to these challenging variants, Gauchian also calls known pathogenic or likely pathogenic GBA variants classified in ClinVar. Gauchian has been tested on Illumina WGS data with standard sequencing depth (>=30X). Gauchian does not work on targeted sequencing data. Please refer to our preprint for more details about the method.
Installation
This Python package is supported for Linux and macOS. It has been tested on CentOS 7.9.2009.
The Python dependencies can be found in requirements.txt
. Installation takes a few seconds.
git clone https://github.com/Illumina/Gauchian
cd Gauchian
python3 setup.py install
Running the program
gauchian --manifest MANIFEST_FILE \
--genome [19/37/38] \
--prefix OUTPUT_FILE_PREFIX \
--outDir OUTPUT_DIRECTORY \
--threads NUMBER_THREADS
The manifest is a text file in which each line should list the absolute path to an input WGS BAM/CRAM file. Full WGS BAM/CRAM files are recommended. If you would like to use a subsetted bamlet, please subset using region files in gauchian/data/GBA_region_*.bed.
For CRAM input, it’s suggested to provide the path to the reference fasta file with --reference
in the command.
Interpreting the output
The program produces a .tsv file in the directory specified by --outDir. The fields are explained below:
Fields in tsv | Explanation |
---|---|
Sample | Sample name |
is_biallelic(GBAP1-like_variant_exon9-11) | Whether the sample is called as biallelic for GBAP1-like variants in exon9-11 |
is_carrier(GBAP1-like_variant_exon9-11) | Whether the sample is called as a carrier for GBAP1-like variants in exon9-11 |
CN(GBA+GBAP1) | Total copy number of GBA+GBAP1 |
deletion_breakpoint_in_GBA | Whether the deletion breakpoint is in GBA gene if a deletion exists |
GBAP1-like_variant_exon9-11 | GBAP1-like variants called in exon9-11, two alleles separated by / |
other_unphased_variants | Other variants called (non-GBAP1-like variants or variants outside of exon9-11) |
A .json file is also produced that contains more information about each sample.
Fields in json | Explanation |
---|---|
Coverage_MAD | Median absolute deviation of depth, measure of sample quality |
Median_depth | Sample median depth |
deletion_CN | CN of the unique region between GBA and GBAP1. This value plus 2 is the total CN |
deletion_CN_raw | Raw normalized depth of the unique region between GBA and GBAP1 |
variant_raw_count | Supporting reads for each variant |
snp_call | GBA copy number call at GBA/GBAP1 differentiating sites |
snp_raw | Raw GBA copy number at GBA/GBAP1 differentiating sites |
haplotypes | Summary of haplotypes assembled across GBA/GBAP1 differentiating sites in Exon9-11 |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file gauchian-1.0.2.tar.gz
.
File metadata
- Download URL: gauchian-1.0.2.tar.gz
- Upload date:
- Size: 26.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.7.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | be2e23c4afb3b6b170706b8864f808c3c5c5f3b1828e4cd76b7f9dc64f023a38 |
|
MD5 | e15cc66a796d432496d6f3f68862bac9 |
|
BLAKE2b-256 | 693d1fcca60bdca179cf600fbe0d1927a916a99875fb10472932c11bcb6b261c |
File details
Details for the file gauchian-1.0.2-py3-none-any.whl
.
File metadata
- Download URL: gauchian-1.0.2-py3-none-any.whl
- Upload date:
- Size: 217.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.7.2
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 85bb886e72963b9cf2f7917a0fb25262b9cbfb63f711e5d6dabf7b58c76a4425 |
|
MD5 | 6b052be6d95fd33ffb710300bae4e733 |
|
BLAKE2b-256 | 4a8c76d09a5651af0dcc386a913d74a29f49d7e5c736dcdd8b91787eb3062949 |