Commit 0cc8977b authored by Peter van 't Hof's avatar Peter van 't Hof
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Convert docs for shiva

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# GATK-pipeline
## Introduction
The GATK-pipeline is build for variant calling on NGS data (preferably Illumina data).
It is based on the <a href="https://www.broadinstitute.org/gatk/guide/best-practices" target="_blank">best practices</a>) of GATK in terms of there approach to variant calling.
The pipeline accepts ```.fastq & .bam``` files as input.
----
## Tools for this pipeline
* <a href="http://broadinstitute.github.io/picard/" target="_blank">Picard tool suite</a>
* [Flexiprep](flexiprep.md)
* <a href="https://www.broadinstitute.org/gatk/" target="_blank">GATK tools</a>:
* Realignertargetcreator
* Indelrealigner
* Baserecalibrator
* Printreads
* Splitncigarreads
* Haplotypecaller
* Variantrecalibrator
* Applyrecalibration
* Genotypegvcfs
* Variantannotator
----
## Example
Note that one should first create the appropriate [configs](../general/config.md).
To get the help menu:
~~~
java -jar Biopet.0.2.0.jar pipeline gatkPipeline -h
Arguments for GatkPipeline:
-outDir,--output_directory <output_directory> Output directory
-sample,--onlysample <onlysample> Only Sample
-skipgenotyping,--skipgenotyping Skip Genotyping step
-mergegvcfs,--mergegvcfs Merge gvcfs
-jointVariantCalling,--jointvariantcalling Joint variantcalling
-jointGenotyping,--jointgenotyping Joint genotyping
-config,--config_file <config_file> JSON config file(s)
-DSC,--disablescatterdefault Disable all scatters
~~~
To run the pipeline:
~~~
java -jar Biopet.0.2.0.jar pipeline gatkPipeline -run -config MySamples.json -config MySettings.json -outDir myOutDir
~~~
To perform a dry run simply remove `-run` from the commandline call.
----
## Multisample and Singlesample
### Multisample
With <a href="https://www.broadinstitute.org/gatk/guide/tagged?tag=multi-sample">multisample</a>
one can perform variantcalling with all samples combined for more statistical power and accuracy.
To Enable this option one should enable the following option `"joint_variantcalling":true` in the settings config file.
### Singlesample
If one prefers single sample variantcalling (which is the default) there is no need of setting the joint_variantcalling inside the config.
The single sample variantcalling has 2 modes as well:
* "single_sample_calling":true (default)
* "single_sample_calling":false which will give the user only the raw VCF, produced with [MpileupToVcf](../tools/MpileupToVcf.md)
----
## Config options
To view all possible config options please navigate to our Gitlab wiki page
<a href="https://git.lumc.nl/biopet/biopet/wikis/GATK-Variantcalling-Pipeline" target="_blank">Config</a>
### Config options
| Config Name | Name | Type | Default | Function |
| ----------- | ---- | ----- | ------- | -------- |
| gatk | referenceFile | String | | |
| gatk | dbsnp | String | | |
| gatk | <samplename>type | String | DNA | |
| gatk | gvcfFiles | Array[String] | | |
**Sample config**
| Config Name | Name | Type | Default | Function |
| ----------- | ---- | ----- | ------- | -------- |
| samples | ---- | String | ---- | ---- |
| SampleID | ---- | String | ---- | ---- |
| libraries | ---- | String | ---- | specify samples within the same library |
| lib_id | ---- | String | ---- | fill in you're library id |
```
{ "samples": {
"SampleID": {
"libraries": {
"lib_id": {"bam": "YoureBam.bam"},
"lib_id": {"bam": "YoureBam.bam"}
}}
}}
```
**Run config**
| Config Name | Name | Type | Default | Function |
| ----------- | ---- | ----- | ------- | -------- |
| run->RunID | ID | String | | Automatic filled by sample json layout |
| run->RunID | R1 | String | | |
| run->RunID | R2 | String | | |
---
### sub Module options
This can be used in the root of the config or within the gatk, within mapping got prio over the root value. Mapping can also be nested in gatk. For options for mapping see: https://git.lumc.nl/biopet/biopet/wikis/Flexiprep-Pipeline
| Config Name | Name | Type | Default | Function |
| ----------- | ---- | ---- | ------- | -------- |
| realignertargetcreator | scattercount | Int | | |
| indelrealigner | scattercount | Int | | |
| baserecalibrator | scattercount | Int | 2 | |
| baserecalibrator | threads | Int | | |
| printreads | scattercount | Int | | |
| splitncigarreads | scattercount | Int | | |
| haplotypecaller | scattercount | Int | | |
| haplotypecaller | threads | Int | 3 | |
| variantrecalibrator | threads | Int | 4 | |
| variantrecalibrator | minnumbadvariants | Int | 1000 | |
| variantrecalibrator | maxgaussians | Int | 4 | |
| variantrecalibrator | mills | String | | |
| variantrecalibrator | hapmap | String | | |
| variantrecalibrator | omni | String | | |
| variantrecalibrator | 1000G | String | | |
| variantrecalibrator | dbsnp | String | | |
| applyrecalibration | ts_filter_level | Double | 99.5(for SNPs) or 99.0(for indels) | |
| applyrecalibration | scattercount | Int | | |
| applyrecalibration | threads | Int | 3 | |
| genotypegvcfs | scattercount | Int | | |
| variantannotator | scattercount | Int | | |
| variantannotator | dbsnp | String | |
----
## Results
The main output file from this pipeline is the final.vcf which is a combined VCF of the raw and discovery VCF.
- Raw VCF: VCF file created from the mpileup file with our own tool called: [MpileupToVcf](../tools/MpileupToVcf.md)
- Discovery VCF: Default VCF produced by the haplotypecaller
### Result files
~~~bash
├─ samples
   ├── <samplename>
   │   ├── run_lib_1
   │   │   ├── <samplename>-lib_1.dedup.bai
   │   │   ├── <samplename>-lib_1.dedup.bam
   │   │   ├── <samplename>-lib_1.dedup.metrics
   │   │   ├── <samplename>-lib_1.dedup.realign.baserecal
   │   │   ├── <samplename>-lib_1.dedup.realign.baserecal.bai
   │   │   ├── <samplename>-lib_1.dedup.realign.baserecal.bam
   │   │   ├── flexiprep
   │   │   └── metrics
   │   ├── run_lib_2
   │   │   ├── <samplename>-lib_2.dedup.bai
   │   │   ├── <samplename>-lib_2.dedup.bam
   │   │   ├── <samplename>-lib_2.dedup.metrics
   │   │   ├── <samplename>-lib_2.dedup.realign.baserecal
   │   │   ├── <samplename>-lib_2.dedup.realign.baserecal.bai
   │   │   ├── <samplename>-lib_2.dedup.realign.baserecal.bam
   │   │   ├── flexiprep
   │   │   └── metrics
   │   └── variantcalling
   │   ├── <samplename>.dedup.realign.bai
   │   ├── <samplename>.dedup.realign.bam
   │   ├── <samplename>.final.vcf.gz
   │   ├── <samplename>.final.vcf.gz.tbi
   │   ├── <samplename>.hc.discovery.gvcf.vcf.gz
   │   ├── <samplename>.hc.discovery.gvcf.vcf.gz.tbi
   │   ├── <samplename>.hc.discovery.variants_only.vcf.gz.tbi
   │   ├── <samplename>.hc.discovery.vcf.gz
   │   ├── <samplename>.hc.discovery.vcf.gz.tbi
   │   ├── <samplename>.raw.filter.variants_only.vcf.gz.tbi
   │   ├── <samplename>.raw.filter.vcf.gz
   │   ├── <samplename>.raw.filter.vcf.gz.tbi
   │   └── <samplename>.raw.vcf
~~~
----
### Best practice
## References
\ No newline at end of file
# Shiva
## Introduction
This pipeline is build for variant calling on NGS data (preferably Illumina data).
It is based on the <a href="https://www.broadinstitute.org/gatk/guide/best-practices" target="_blank">best practices</a>) of GATK in terms of there approach to variant calling.
The pipeline accepts ```.fastq & .bam``` files as input.
----
## Tools for this pipeline
* <a href="http://broadinstitute.github.io/picard/" target="_blank">Picard tool suite</a>
* [Flexiprep](flexiprep.md)
* <a href="https://www.broadinstitute.org/gatk/" target="_blank">GATK tools</a>:
* GATK
* Freebayes
* Bcftools
* Samtools
----
## Example
Note that one should first create the appropriate [configs](../general/config.md).
To get the help menu:
~~~
java -jar </path/to/biopet.jar> pipeline shiva -h
Arguments for Shiva:
-sample,--onlysample <onlysample> Only Sample
-config,--config_file <config_file> JSON config file(s)
-DSC,--disablescatterdefault Disable all scatters
~~~
To run the pipeline:
~~~
java -jar </path/to/biopet.jar> pipeline shiva -run -config MySamples.json -config MySettings.json
~~~
To perform a dry run simply remove `-run` from the commandline call.
----
## Variantcaller
At this moment the following variantcallers modes can be used
* haplotypecaller
* haplotypecaller_gvcf
* haplotypecaller_allele
* unifiedgenotyper
* unifiedgenotyper_allele
* bcftools
* freebayes
* raw
----
## Multisample and Singlesample
### Multisample
With <a href="https://www.broadinstitute.org/gatk/guide/tagged?tag=multi-sample">multisample</a>
one can perform variantcalling with all samples combined for more statistical power and accuracy.
### Singlesample
If one prefers single sample variantcalling (which is the default) there is no need of setting the joint_variantcalling inside the config.
The single sample variantcalling has 2 modes as well:
----
## Config options
To view all possible config options please navigate to our Gitlab wiki page
<a href="https://git.lumc.nl/biopet/biopet/wikis/GATK-Variantcalling-Pipeline" target="_blank">Config</a>
### Config options
| Config Name | Name | Type | Default | Function |
| ----------- | ---- | ----- | ------- | -------- |
| shiva | reference | String | | reference to align to |
| shiva | dbsnp | String | | vcf file of dbsnp records |
| shiva | variantcallers | List[String] | | variantcaller to use, see list |
| shiva | multisample_sample_variantcalling | Boolean | true | |
| shiva | single_sample_variantcalling | Boolean | false | |
| shiva | library_variantcalling | Boolean | false | |
**Config example**
```json
{
"samples": {
"SampleID": {
"libraries": {
"lib_id_1": { "bam": "YoureBam.bam" },
"lib_id_2": { "R1": "file_R1.fq.gz", "R2": "file_R2.fq.gz" }
}
}
},
"variantcallers": [ "haplotypecaller", "unifiedgenotyper" ],
"output_dir": "<output directory>"
}
```
## References
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