Metadata-Version: 2.1
Name: vcfstats
Version: 0.4.2
Summary: Powerful statistics for VCF files
Home-page: https://github.com/pwwang/vcfstats
License: MIT
Author: pwwang
Author-email: pwwang@pwwang.com
Requires-Python: >=3.8,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Dist: cyvcf2 (<1.0.0)
Requires-Dist: datar (>=0.9,<0.10)
Requires-Dist: lark-parser (>=0.12,<0.13)
Requires-Dist: numpy (>=1.22,<2.0)
Requires-Dist: plotnine (>=0.8,<0.9)
Requires-Dist: plotnine-prism (>=0.0,<0.1)
Requires-Dist: py (>=1.10,<2.0)
Requires-Dist: pyparam (>=0.5.1,<0.6.0)
Requires-Dist: python-slugify (>=6,<7)
Requires-Dist: rich (>=12,<13)
Project-URL: Repository, https://github.com/pwwang/vcfstats
Description-Content-Type: text/markdown

# vcfstats - powerful statistics for VCF files

[![Pypi][1]][2] [![Github][3]][4] [![PythonVers][5]][2] [![docs][6]][13] ![github action][7] [![Codacy][9]][10] [![Codacy coverage][11]][10]

[Documentation][13] | [CHANGELOG][12]

## Motivation
There are a couple of tools that can plot some statistics of VCF files, including [`bcftools`][14] and [`jvarkit`][15]. However, none of them could:
1. plot specific metrics
2. customize the plots
3. focus on variants with certain filters

R package [`vcfR`][19] can do some of the above. However, it has to load entire VCF into memory, which is not friendly to large VCF files.

## Installation
```shell
pip install -U vcfstats
```

Or run with docker or singularity:
```shell
docker run --rm justold/vcfstats:latest vcfstats
# or
singularity run docker://justold/vcfstats:latest vcfstats
```

## Gallery

### Number of variants on each chromosome

```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1) ~ CONTIG' \
	--title 'Number of variants on each chromosome' \
	--config examples/config.toml
```

![Number of variants on each chromosome](examples/number-of-variants-on-each-chromosome.col.png)

#### Changing labels and ticks

`vcfstats` uses [`plotnine`][17] for plotting, read more about it on how to specify `--ggs` to modify the plots.

```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1) ~ CONTIG' \
	--title 'Number of variants on each chromosome (modified)' \
	--config examples/config.toml \
	--ggs 'scale_x_discrete(name ="Chromosome", \
		limits=["1","2","3","4","5","6","7","8","9","10","X"]); \
		ylab("# Variants")'
```

![Number of variants on each chromosome (modified)](examples/number-of-variants-on-each-chromosome-modified.col.png)

#### Number of variants on first 5 chromosome

```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1) ~ CONTIG[1,2,3,4,5]' \
	--title 'Number of variants on each chromosome (first 5)' \
	--config examples/config.toml
# or
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1) ~ CONTIG[1-5]' \
	--title 'Number of variants on each chromosome (first 5)' \
	--config examples/config.toml
# or
# require vcf file to be tabix-indexed.
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1) ~ CONTIG' \
	--title 'Number of variants on each chromosome (first 5)' \
	--config examples/config.toml -r 1 2 3 4 5
```

![Number of variants on each chromosome (first 5)](examples/number-of-variants-on-each-chromosome-first-5.col.png)

### Number of substitutions of SNPs
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1, VARTYPE[snp]) ~ SUBST[A>T,A>G,A>C,T>A,T>G,T>C,G>A,G>T,G>C,C>A,C>T,C>G]' \
	--title 'Number of substitutions of SNPs' \
	--config examples/config.toml
```
![Number of substitutions of SNPs](examples/number-of-substitutions-of-snps.col.png)

#### Only with SNPs PASS all filters

```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1, VARTYPE[snp]) ~ SUBST[A>T,A>G,A>C,T>A,T>G,T>C,G>A,G>T,G>C,C>A,C>T,C>G]' \
	--title 'Number of substitutions of SNPs (passed)' \
	--config examples/config.toml \
	--passed
```

![Number of substitutions of SNPs (passed)](examples/number-of-substitutions-of-snps-passed.col.png)

### Alternative allele frequency on each chromosome
```shell
# using a dark theme
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'AAF ~ CONTIG' \
	--title 'Allele frequency on each chromosome' \
	--config examples/config.toml --ggs 'theme_dark()'
```

![Allele frequency on each chromosome](examples/allele-frequency-on-each-chromosome.violin.png)

#### Using boxplot
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'AAF ~ CONTIG' \
	--title 'Allele frequency on each chromosome (boxplot)' \
	--config examples/config.toml \
	--figtype boxplot
```

![Allele frequency on each chromosome](examples/allele-frequency-on-each-chromosome.boxplot.png)

#### Using density plot/histogram to investigate the distribution:
You can plot the distribution, using density plot or histogram
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'AAF ~ CONTIG[1,2]' \
	--title 'Allele frequency on chromosome 1,2' \
	--config examples/config.toml \
	--figtype density
```
![Allele frequency on chromosome 1,2](examples/allele-frequency-on-chromosome-1-2.density.png)

### Overall distribution of allele frequency
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'AAF ~ 1' \
	--title 'Overall allele frequency distribution' \
	--config examples/config.toml
```
![Overall allele frequency distribution](examples/overall-allele-frequency-distribution.histogram.png)

#### Excluding some low/high frequency variants
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'AAF[0.05, 0.95] ~ 1' \
	--title 'Overall allele frequency distribution (0.05-0.95)' \
	--config examples/config.toml
```
![Overall allele frequency distribution](examples/overall-allele-frequency-distribution-0-05-0-95.histogram.png)

### Counting types of variants on each chromosome
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1, group=VARTYPE) ~ CHROM' \
	# or simply
	# --formula 'VARTYPE ~ CHROM' \
	--title 'Types of variants on each chromosome' \
	--config examples/config.toml
```

![Types of variants on each chromosome](examples/types-of-variants-on-each-chromosome.col.png)

#### Using bar chart if there is only one chromosome
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'COUNT(1, group=VARTYPE) ~ CHROM[1]' \
	# or simply
	# --formula 'VARTYPE ~ CHROM[1]' \
	--title 'Types of variants on chromosome 1' \
	--config examples/config.toml \
	--figtype pie
```
![Types of variants on chromosome 1](examples/types-of-variants-on-chromosome-1.pie.png)

#### Counting variant types on whole genome
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	# or simply
	# --formula 'VARTYPE ~ 1' \
	--formula 'COUNT(1, group=VARTYPE) ~ 1' \
	--title 'Types of variants on whole genome' \
	--config examples/config.toml
```
![Types of variants on whole genome](examples/types-of-variants-on-whole-genome.col.png)

### Counting type of mutant genotypes (HET, HOM_ALT) for sample 1 on each chromosome
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	# or simply
	# --formula 'GTTYPEs[HET,HOM_ALT]{0} ~ CHROM' \
	--formula 'COUNT(1, group=GTTYPEs[HET,HOM_ALT]{0}) ~ CHROM' \
	--title 'Mutant genotypes on each chromosome (sample 1)' \
	--config examples/config.toml
```

![Mutant genotypes on each chromosome](examples/mutant-genotypes-on-each-chromosome-sample-1.col.png)


### Exploration of mean(genotype quality) and mean(depth) on each chromosome for sample 1
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'MEAN(GQs{0}) ~ MEAN(DEPTHs{0}, group=CHROM)' \
	--title 'GQ vs depth (sample 1)' \
	--config examples/config.toml
```
![GQ vs depth (sample 1)](examples/gq-vs-depth-sample-1.scatter.png)

### Exploration of depths for sample 1,2
```shell
vcfstats --vcf examples/sample.vcf \
	--outdir examples/ \
	--formula 'DEPTHs{0} ~ DEPTHs{1}' \
	--title 'Depths between sample 1 and 2' \
	--config examples/config.toml
```
![Depths between sample 1 and 2](examples/depths-between-sample-1-and-2.scatter.png)


See more examples:

https://github.com/pwwang/vcfstats/issues/15#issuecomment-1029367903

[1]: https://img.shields.io/pypi/v/vcfstats?style=flat-square
[2]: https://pypi.org/project/vcfstats/
[3]: https://img.shields.io/github/v/tag/pwwang/vcfstats?style=flat-square
[4]: https://github.com/pwwang/vcfstats
[5]: https://img.shields.io/pypi/pyversions/vcfstats?style=flat-square
[6]: https://img.shields.io/github/workflow/status/pwwang/vcfstats/Build%20Docs?label=docs&style=flat-square
[7]: https://img.shields.io/github/workflow/status/pwwang/vcfstats/Build%20and%20Deploy?style=flat-square
[8]: https://travis-ci.org/pwwang/vcfstats
[9]: https://img.shields.io/codacy/grade/c8c8bfa8c5e9443bbf268a0a7c6f206d?style=flat-square
[10]: https://app.codacy.com/gh/pwwang/vcfstats/
[11]: https://img.shields.io/codacy/coverage/c8c8bfa8c5e9443bbf268a0a7c6f206d?style=flat-square
[12]: https://pwwang.github.io/vcfstats/CHANGELOG/
[13]: https://pwwang.github.io/vcfstats/
[14]: https://samtools.github.io/bcftools/bcftools.html#stats
[15]: http://lindenb.github.io/jvarkit/VcfStatsJfx.html
[16]: https://www.r-project.org/
[17]: https://plotnine.readthedocs.io/en/stable/
[18]: https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html
[19]: https://knausb.github.io/vcfR_documentation/visualization_1.html

