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https://github.com/brentp/somalier

fast sample-swap and relatedness checks on BAMs/CRAMs/VCFs/GVCFs... "like damn that is one smart wine guy"
https://github.com/brentp/somalier

bioinformatics cancer-genomics genomics

Last synced: 25 days ago
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fast sample-swap and relatedness checks on BAMs/CRAMs/VCFs/GVCFs... "like damn that is one smart wine guy"

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README 

        
# somalier: extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF



[![Actions Status](https://github.com/brentp/somalier/workflows/Docker%20Image%20CI/badge.svg)](https://github.com/brentp/somalier/actions)

[![Cite](https://img.shields.io/badge/cite-genome%20medicine-blue)](https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-020-00761-2)

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/somalier/README.html)



## Quick Start 

`somalier` makes checking any number of samples for identity easy **directly from the alignments** or from jointly-called VCFs:



The first step is to extract sites. For **VCF** just use:

```

somalier extract -d extracted/ --sites sites.vcf.gz -f /data/human/g1k_v37_decoy.fa $cohort.vcf.gz

```



with a sites file from [releases](https://github.com/brentp/somalier/releases/latest)



For **BAM** or **CRAM**, use:

This is parallelizable by sample via cluster or cloud, but here, using a for loop:

```

for f in *.cram; do

    somalier extract -d extracted/ --sites sites.vcf.gz -f /data/human/g1k_v37_decoy.fa $f

done

```



`--sites` is a VCF of known polymorphic sites in VCF format. A good set is provided in

the [releases](https://github.com/brentp/somalier/releases) but any set of common variants will work.



> :warning: `somalier` can work on GVCF and individual VCFs, but it is

> recommended to extract from bam/cram when possible. It is also good to

> extract from a jointly-called VCF/BCF when only looking within that cohort.

> While extracting from a single-sample VCF is possible (with --unknown) and

> GVCF is also supported, these options are less accurate and more prone to

> problems.



The next step is to calculate relatedness on the extracted data:



```

somalier relate --ped $pedigree extracted/*.somalier

```

This will create text and interactive HTML output

that makes it fast and easy to detect mismatched samples and sample-swaps.

The files created are:

+ `{output_prefix}.samples.tsv # creates a .ped like file with extra QC columns

+ `{output_prefix}.pairs.tsv # shows IBS for all possible sample pairs

+ `{output_prefix}.groups.tsv # shows pairs of samples above a certain relatedness

+ `{output_prefix}.html # interactive html



Example html output is [here](https://brentp.github.io/somalier/ex.html)



Note that the `somalier relate` command runs extremely quickly (< 2 seconds for 600 samples and ~1 minute for 4,500 samples) so it's possible

to add/remove samples or adjust a pedigree file and re-run iteratively.



For example to add the **n + 1th** samples, just run `somalier extract` on the new sample and then re-use

the already extracted data from the `n` original samples.



For *huge* sample-sets, if you run into a bash error for *argument list too long*, you can pass the somalier files as quoted

glob strings like:  `"/path/to/set-a/*.somalier" "/path/to/set-b/*.somalier"`.



## Example Output



+ Interactive output from `somalier relate` is [here](https://brentp.github.io/somalier/ex.html)

+ Interactive output from `somalier ancestry` is [here](https://brentp.github.io/somalier/ex.somalier-ancestry.html)



## Infer



`somalier` can also infer first-degree relationships (parent-child) when both-parents

are present and can often build entire pedigrees on high-qualty data. To do this, use

 `somalier relate --infer ...` and the **samples.tsv** output will be a pedigree file

indicating the inferred relationships.



See [wiki](https://github.com/brentp/somalier/wiki/pedigree-inference) for more detail.



## Usage



The usage is also described above. Briefly, after downloading the somalier binary and a sites vcf from the [releases](https://github.com/brentp/somalier/releases/latest) run:

```

somalier extract -d cohort/ --sites sites.hg38.vcf.gz -f $reference $sample.bam

```

for each sample to create a small binary file of the ref and alt counts for the variants listed

in sites.hg38.vcf.gz.



for a vcf, run:

```

somalier extract -d cohort/ --sites sites.hg38.vcf.gz -f $reference $cohort.bcf

```



`somalier` can `extract` from a multi or single-sample VCF or a GVCF. This will be much faster, in cases where it's available,

this would look like:



```

somalier extract -d extracted/ --sites sites.vcf.gz -f /data/human/g1k_v37_decoy.fa joint.vcf.gz

```



following this, there will be a `$sample.somalier` file for each sample in the `joint.vcf.gz`



Note that `somalier` uses the `AD` field to extract depth information. If that FORMAT field is not present in the

header, then it will use the genotypes only and use a total depth of 20 (10,10 for heterozygote), etc.



Then run:

```

somalier relate --ped $pedigree_file cohort/*.somalier

```

This will create an html file for QC in a few seconds. 



Note that if a new sample is added to the cohort, it's only necessary to perform

the `extract` step on that sample and then run the (fast) `relate` step again with all

of the extracted files.



## Extended Usage

For each command of somalier, extended parameters are listed in `--help` of each subcommand.

```

$./somalier --help

Commands:

  extract      :   extract genotype-like information for a single sample from VCF/BAM/CRAM.

  relate       :   aggregate `extract`ed information and calculate relatedness among samples.

  ancestry     :   perform ancestry prediction on a set of samples, given a set of labeled samples

  find-sites   :   create a new sites.vcf.gz file from a population VCF (this is rarely needed).

```

### somalier extract



extract genotype-like information for a single-sample at selected sites



```

Usage:

  somalier extract [options] sample_file



Arguments:

  sample_file      single-sample CRAM/BAM/GVCF file or multi/single-sample VCF from which to extract



Options:

  -s, --sites=SITES          sites vcf file of variants to extract

  -f, --fasta=FASTA          path to reference fasta file

  -d, --out-dir=OUT_DIR      path to output directory (default: .)

  --sample-prefix=SAMPLE_PREFIX

                             prefix for the sample name stored inside the digest

```

### somalier relate



calculate relatedness among samples from extracted, genotype-like information



```

Usage:

  somalier relate [options] [extracted ...]



Arguments:

  [extracted ...]  $sample.somalier files for each sample. the first 10 are tested as a glob patterns



Options:

  -g, --groups=GROUPS        optional path  to expected groups of samples (e.g. tumor normal pairs).

specified as comma-separated groups per line e.g.:

    normal1,tumor1a,tumor1b

    normal2,tumor2a

  --sample-prefix=SAMPLE_PREFIX

                             optional sample prefixes that can be removed to find identical samples. e.g. batch1-sampleA batch2-sampleA

  -p, --ped=PED              optional path to a ped/fam file indicating the expected relationships among samples.

  -d, --min-depth=MIN_DEPTH  only genotype sites with at least this depth. (default: 7)

  --min-ab=MIN_AB            hets sites must be between min-ab and 1 - min_ab. set this to 0.2 for RNA-Seq data (default: 0.3)

  -u, --unknown              set unknown genotypes to hom-ref. it is often preferable to use this with VCF samples that were not jointly called

  -i, --infer                infer relationships (https://github.com/brentp/somalier/wiki/pedigree-inference)

  -o, --output-prefix=OUTPUT_PREFIX

                             output prefix for results. (default: somalier)

```



Note that for large cohorts, by default, `somalier relate` will subset to interesting sample-pairs so as not to

balloon the size of the output. By default, pairs that are expected to be unrelated and have a relatedness <= 0.05.

If you wish to force all samples to be reported, then set the environment variable `SOMALIER_REPORT_ALL_PAIRS` to any non-empty

value, e.g. `export SOMALIER_REPORT_ALL_PAIRS=1`



## find-sites



To create a set of new sites, use `somalier find-sites` on a population VCF. More info on this tool is available in [the wiki](https://github.com/brentp/somalier/wiki/find-sites)



## Install



Somalier is available via bioconda, see [here](https://bioconda.github.io/recipes/somalier/README.html).



Alternatively, you can get a static binary from [here](https://github.com/brentp/somalier/releases).



Users can also get a docker image [here](https://hub.docker.com/r/brentp/somalier/tags)

which contains htslib and a somalier binary ready-for-use.



## How it works



`somalier` takes a list of known polymorphic sites. Even a few hundred (or dozen) sites

can be a very good indicator of relatedness. The best sites are those with a population

allele frequency close to 0.5 as that maximizes the probability that any 2 samples will differ.

A list of such sites is provided in the [releases](https://github.com/brentp/somalier/releases)

for GRCh37 and hg38.



In order to quickly calculate genotypes at these sites, `somalier` assays the exact base.

The extraction step is done directly from the bam/cram files 1 sample at a time.



The `relate` step is run on the output of the `extract` commands. It runs extremely quickly

so that new samples can be added and compared. It uses 3 bit-vectors per sample for hom-ref,

het, hom-alt. Each bitvector is a sequence of 64 bit integers where each bit is set if

the variant at that index in the sample is for example, heterozygous. With this setup,

we can use fast bitwise operations and [popcount](https://en.wikichip.org/wiki/population_count)

hardware instructions to calculate relatedness extremely quickly.



For each sample-pair, it reports:

1. IBS0 -- the number of sites where one sample is hom-ref and another is hom-alt

2. IBS2 -- the number of sites where the samples have the same genotype

3. shared-hets -- the number of sites where both samples are heterozygotes

4. shared-hom-alts -- the number of sites where both samples are homozygous alternate



These are used to calculate [relatedness](https://en.wikipedia.org/wiki/Coefficient_of_relationship)

and a measure of relatedness that is unaffected by loss-of-heterozygosity that is often seen in some 

cancers. The interactive output allows toggling between any of these measures.



It also reports depth information and the count of `HET`, `HOM_REF`, `HOM_ALT`, and `unknown` genotypes for each sample

along with a number of metrics that are useful for general QC.



## Example



![example](https://user-images.githubusercontent.com/1739/43783575-4863f13c-9a1f-11e8-9cf8-622f784edc69.png)



Here, each point is a pair of samples. We can see that the expected identical sample-pairs (e.g. tumor-normal pairs) specified by the user

and drawn in red mostly cluster together on the right. Unrelateds cluster on the lower left. The sample-swaps are the blue points that cluster with

the red. In the somalier output, the user can **hover to see which sample-pairs are involved each point**



## Ancestry Estimate



`somalier` can predict ancestry on a set of query samples given a set of labelled samples. You can read more about this in [the wiki](https://github.com/brentp/somalier/wiki/ancestry)



## Usage



Usage is intentionally very simple and running `somalier extract` or `somalier relate` will give sufficient help for nearly

all cases.



By default `somalier` will only consider variants that have a "PASS" or "RefCall" FILTER. To extend this list, set

the environment variable `SOMALIER_ALLOWED_FILTERS` to a comma-delimited list of additional filters to allow.



by default sites with an allele balance < 0.01 will be considered homozygous reference. To adjust this, use e.g. : 

`SOMALIER_AB_HOM_CUTOFF=0.04 somalier relate ...`

 

## Other Work



https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499645/



https://academic.oup.com/bioinformatics/article/33/4/596/2624551



## Acknowledgement



This work was motivated by interaction and discussions with Preeti Aahir and several

early users who provided valuable feedback.