This pipeline performs population genetics analyses (such as identifying shared haplotypes and divergent regions) at the isotype level. The VCFs output from this pipeline are used within the lab and also released to the world via CeNDR.
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parameters description Set/Default
========== =========== ========================
--debug Use --debug to indicate debug mode (optional)
--vcf_folder Folder to hard and soft filtered vcf (required)
--sample_sheet TSV with column iso-ref strain, bam, bai (no header) (required)
--species Species: 'c_elegans', 'c_tropicalis' or 'c_briggsae' c_elegans
--output Output folder name. popgen-date (in current folder)
- The latest update requires Nextflow version 20.0+. On QUEST, you can access this version by loading the
nf20
conda environment prior to running the pipeline command:
module load python/anaconda3.6
source activate /projects/b1059/software/conda_envs/nf20_env
Alternatively you can update Nextflow by running:
nextflow self-update
This pipeline currently only supports analysis on Quest, cannot be run locally
For more info about running Nextflow pipelines in the Andersen Lab, check out this page
This command uses a test dataset
nextflow run andersenlab/post-gatk-nf --debug
You should run this in a screen session.
There are now three ways to run this pipeline:
-profile standard
(default): runs original processes including subseting VCF and divergent and haplotype calls.- sample_sheet, vcf_folder, (species)
-profile pca
: does not run the original post-gatk processes, only the PCA analysis. Note: requires different parameters- snv_vcf, species, anc, eigen_ld, pops
-profile standard --pca
: runs all processes including subseting VCF, divergent and haplotype calls, PCA analysis of isotypes. Requires additional parameters relating to PCA- sample_sheet, vcf_folder, species, anc, eigen_ld
- Note: the
-profile standard
is optional, just adding the--pca
param is enough.
nextflow run andersenlab/post-gatk-nf --vcf <path_to_vcf> --sample_sheet <path_to_sample_sheet>
You should use --debug true
for testing/debugging purposes. This will run the debug test set (located in the test_data
folder).
For example:
nextflow run andersenlab/post-gatk-nf --debug -resume
Using --debug
will automatically set the sample sheet to test_data/sample_sheet.tsv
You can debug the PCA pipeline with the following data/command:
nextflow run main.nf --vcf ./test_data/WI.20220404.hard-filter.vcf.gz --species c_elegans --sample_sheet ./test_data/sample_sheet_2.tsv --eigen_ld 0.8,0.6 --anc XZ2019 --pca -resume
A custom sample sheet can be specified using --sample_sheet
. The sample sheet
is generated from the sample sheet used as input for wi-gatk-nf
with only columns for strain, bam, and bai subsetted. Make sure to remove any strains that you do not want to include in this analysis. (i.e. subset to keep only ISOTYPE strains)
Remember that in --debug
mode the pipeline will use the sample sheet located in test_data/sample_sheet.tsv
.
Important: There is no header for the sample sheet!
The sample sheet
has the following columns:
- strain - the name of the strain
- bam - name of the bam alignment file
- bai - name of the bam alignment index file
Note: As of 20210501, bam and bam.bai files for all strains of a particular species can be found in one singular location: /projects/b1059/data/{species}/WI/alignments/
so there is no longer need to provide the location of the bam files.
Path to the folder containing both the hard-filtered and soft-filtered vcf outputs from wi-gatk
. VCF should contain ALL strains, the first step will be to subset isotype reference strains for further analysis.
Note: This should be the path to the folder, we want to isotype-subset both hard and soft filtered VCFs. For example: --vcf_folder /projects/b1059/projects/Katie/wi-gatk/WI-20210121/variation/
or --vcf_folder /projects/b1059/data/c_elegans/WI/variation/20210121/vcf/
default = c_elegans
Options: c_elegans, c_briggsae, or c_tropicalis
The PCA profile can be run either with the full pipeline of independently. To run only PCA use -profile pca
The input VCF is filtered to bi-alleleic snps with no missing genotypes. A LD filtering threshold is required and LD filtering is performed using plink. You can also filter for singletons by specifying the --singletons
PCA is performed using smartPCA. Parameters to control outlier threshold or removal iterations are desribed below.
File path to VCF
Strain list to filter VCF for PCA analysis. No header:
AB1 |
---|
CB4856 |
ECA788 |
Note: If you run the standard profile with pca this file will be automatically generated to include all isotypes.
LD thresholds to test for PCA. Can provide multiple with --eigen_ld 0.8,0.6,0.4
Number of smartPCA outlier removal iterations --outlier_iterations 5,10,15,20
Default is 5
Wether or not to filter for singletons in PCA `--singletons
default - popgen-YYYYMMDD
A directory in which to output results. If you have set --debug true
, the default output directory will be popgen-YYYYMMDD-debug
.
├── ANNOTATE_VCF
│ ├── ANC.bed.gz
│ ├── ANC.bed.gz.tbi
│ ├── Ce330_annotated.vcf.gz
| └── Ce330_annotated.vcf.tbi
├── EIGESTRAT
│ └── LD_{eigen_ld}
│ ├── INPUT_FILES
│ │ └── *
│ ├── OUTLIER_REMOVAL
│ │ ├── eigenstrat_outliers_removed_relatedness
│ │ ├── eigenstrat_outliers_removed_relatedness.id
│ │ ├── eigenstrat_outliers_removed.evac
│ │ ├── eigenstrat_outliers_removed.eval
│ │ ├── logfile_outlier.txt
│ │ └── TracyWidom_statistics_outlier_removal.tsv
│ └── NO_REMOVAL
│ └── same as outlier_removal
├── pca_report.html
├── divergent_regions
│ ├── Mask_DF
│ │ └── [strain]_Mask_DF.tsv
| └── divergent_regions_strain.bed
├── haplotype
│ ├── haplotype_length.pdf
│ ├── sweep_summary.tsv
│ ├── max_haplotype_genome_wide.pdf
│ ├── haplotype.pdf
│ ├── haplotype.tsv
│ ├── [chr].ibd
│ └── haplotype_plot_df.Rda
├── tree
│ ├── WI.{date}.hard-filter.isotype.min4.tree
│ ├── WI.{date}.hard-filter.isotype.min4.tree.pdf
│ ├── WI.{date}.hard-filter.min4.tree
│ └── WI.{date}.hard-filter.min4.tree.pdf
├── NemaScan
│ ├── strain_isotype_lookup.tsv
│ ├── div_isotype_list.txt
│ ├── haplotype_df_isotype.bed
│ ├── divergent_bins.bed
│ └── divergent_df_isotype.bed
└── variation
├── WI.{date}.small.hard-filter.isotype.vcf.gz
├── WI.{date}.small.hard-filter.isotype.vcf.gz.tbi
├── WI.{date}.hard-filter.isotype.SNV.vcf.gz
├── WI.{date}.hard-filter.isotype.SNV.vcf.gz.tbi
├── WI.{date}.soft-filter.isotype.vcf.gz
├── WI.{date}.soft-filter.isotype.vcf.gz.tbi
├── WI.{date}.hard-filter.isotype.vcf.gz
└── WI.{date}.hard-filter.isotype.vcf.gz.tbi
andersenlab/postgatk
(link): Docker image is created within this pipeline using GitHub actions. Whenever a change is made toenv/postgatk.Dockerfile
or.github/workflows/build_postgatk_docker.yml
GitHub actions will create a new docker image and push if successfulandersenlab/tree
(link): Docker image is created within this pipeline using GitHub actions. Whenever a change is made toenv/tree.Dockerfile
or.github/workflows/build_tree_docker.yml
GitHub actions will create a new docker image and push if successfulandersenlab/pca
(link): Docker image is created within this pipeline using GitHub actions. Whenever a change is made toenv/pca.Dockerfile
or.github/workflows/build_pca_docker.yml
GitHub actions will create a new docker image and push if successfulandersenlab/r_packages
(link): Docker image is created manually, code can be found in the dockerfile repo.