https://github.com/brentp/hts-nim-tools
useful command-line tools written to showcase hts-nim
Science Score: 13.0%
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○Scientific vocabulary similarity
Low similarity (11.0%) to scientific vocabulary
Keywords
Repository
useful command-line tools written to showcase hts-nim
Basic Info
- Host: GitHub
- Owner: brentp
- License: mit
- Language: Nim
- Default Branch: master
- Homepage: https://github.com/brentp/hts-nim
- Size: 11.7 KB
Statistics
- Stars: 50
- Watchers: 4
- Forks: 6
- Open Issues: 3
- Releases: 0
Topics
Metadata Files
README.md
hts-nim-tools
This repository contains a number of tools created with hts-nim intended
to serve as examples for using hts-nim as well as to be useful tools.
These tools are:
``` hts-nim utility programs. version: $version
• bam-filter : filter BAM/CRAM/SAM files with a simple expression language
• count-reads : count BAM/CRAM reads in regions given in a BED file
• vcf-check : check regions of a VCF against a background for missing chunks
```
each of these is described in more detail below.
bam-filter
Use simple expressions to filter a BAM/CRAM file:
``` bam-filter
Usage: bam-filter [options]
-t --threads
valid expressions may access the bam attibutes:
-
mapq/start/pos/end/flag/insert_size(where pos is the 1-based start) is_alignedis_read1is_read2is_supplementaryis_secondaryis_dupis_qcfailis_reverseis_mate_reverseis_pairis_proper_pairis_mate_unmappedis_unmapped
to use aux tags, indicate them prefixed with 'tag_', e.g.:
tag_NM < 2. Any tag present in the bam can be used in this manner.
example:
bam-filter "tag_NM == 2 && tag_RG == 'SRR741410' && is_proper_pair" tests/HG02002.bam
count-reads
Count reads reports the number of reads overlapping each interval in a BED file.
``` count-reads
Usage: count-reads [options]
Arguments:
Options:
-t --threads
This is output a line with a count of reads for each line in
vcf-check
vcf-check is useful as a quality control for large projects which have done variant calling in regions
where each region is called in parallel. With many regions, and large projects, some regions can error and
this might be unknown to the analyst.
This tools takes a background VCF, such as gnomad, that has full genome (though in some cases, users will instead want whole exome) coverage and uses that as an expectation of variants. If the background has many variants across a long stretch of genome where the query VCF has no variation, we can expect that region is missed in the query VCF.
``` Check a VCF against a background to make sure that there are no large missing chunks.
vcf-check
Usage: vcf-check [options]
Arguments:
Options:
-c --chunk
This will output a tab-delimited file of chrom\tposition\tbackground-count\tquery-count.
The user can find regions that might be problematic by plotting or with some simple awk commands.
Owner
- Name: Brent Pedersen
- Login: brentp
- Kind: user
- Location: Oregon, USA
- Twitter: brent_p
- Repositories: 220
- Profile: https://github.com/brentp
Doing genomics
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