CH Toolkit

The CH Toolkit is a collection of utilities and tools created by Irenaeus Chan (chani@wustl.edu) and Indraniel for the purpose of handling and maintaing variants called by the ArCH Pipeline.

Sample Alignment & Variant Calling Pipeline

Variant Calling is performed using two separate Variant Callers: GATK's Mutect2 and AstraZeneca's VarDict

To improve on cost and runtime performance, only genomic regions where Mutect2 successfully called and passed variants are used as input BED windows to VarDict.

Details behind this WDL workflow can be found here under the ArCH WGS Variant Calling Pipeline.

The subsequent variants called by both callers are then sanitized, normalized, and filtered for common Germline variants before being used as inputs for this toolkit.

Variant Annotation

To consolidate as much information as possible prior to filtering for CH variants. Several annotation steps must be performed including:

• VEP - The effect of variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions.
• Panel of Normal (PoN) Pileup - Estimation of the statistical noise within a given region or location from sequencing
• AnnotatePD (RScript) - The classification of CH variants through prior large-scale sequencing projects and population data including OncoKB, COSMIC, gnomAD, etc.

Variant Processing Pipeline

While this tool is meant to be run as a stand-alone infrastructure, for the purposes of automation, a WDL workflow has been written with inputs being simply the VCF files produced from Mutect2 and VarDict, sample phenotype information, and the local database filepath for the storage and maintainence of the variant database.

Installation

Please use pip to install ch-toolkit.

If you want to try the latest bleeding edge, run the following command:

pip install git+https://github.com/kbolton-lab/ch-toolkit.git@main

For a stable docker image of ch-toolkit, please visit Docker Hub.

CLI

Usage: ch-toolkit [OPTIONS] COMMAND [ARGS]...

  A collection of db related tools for handling sample data.

Options:
  --version   Show the version and exit.
  -h, --help  Show this message and exit.

Commands:
  calculate-fishers-test  Updates the variants inside Mutect or Vardict tables
                          with p-value from Fisher's Exact Test
  chromosome-to-caller    Combines all chromosome databases into a single
                          <Mutect|Vardict> database
  database-to-chromosome  Splits <Mutect|Vardict|Variant|Annotation|Pileup>
                          database into individual chromosomes
  dump-annotations        dumps all variant annotations inside duckdb into a
                          CSV file
  dump-ch                 Outputs CH Variants from Database
  dump-variants           dumps all variants inside duckdb into a VCF file
  dump-variants-pileup    dumps all variants inside duckdb into a VCF file
                          that needs pileup
  import-annotate-pd      annotates variants with their pathogenicity
  import-pon-pileup       updates variants inside duckdb with PoN pileup
                          information
  import-sample-variants  Register the variants for a VCF file into a variant
                          database
  import-sample-vcf       import a vcf file into sample variant database
  import-samples          Loads a CSV containing samples into samples database
  import-vep              updates variants inside duckdb with VEP information
  merge-batch-variants    Combines all sample variant databases into a single
                          database
  merge-batch-vcf         Combines all sample vcfs databases into a single
                          database
  reduce-db               Reduces the size of the mutect_db and vardict_db
                          databases to only CH possible variants

Workflow Diagram

Functions

Importing Samples

import-samples
Goal:	Create the samples.db database which will contain the information for the samples
Input:	A CSV file containing the information relevant to the samples being processed
Output:	samples.db database

  ch-toolkit import-samples \
    --samples washu-cad-1.csv \
    --sdb database/samples.db \
    --batch-number 1

Importing Variants for a Single Sample

import-sample-variants
Goal:	Create individual sample.variant.db database for each sample that will contain the variant specific information
Input:	Sample VCF file containing the information about the variants
Output:	sample.variant.db database

  ch-toolkit import-sample-variants \
    --input-vcf mutect.sample_name.vcf.gz \
    --vdb variant_databases/mutect.sample_name.db \
    --batch-number 1

  ch-toolkit import-sample-variants \
    --input-vcf vardict.sample_name.vcf.gz \
    --vdb variant_databases/vardict.sample_name.db \
    --batch-number 1

Create a Single Centralized Variants Database from all Individual Sample Variants Databases

merge-batch-variants
Goal:	Create a single variants.db that will contain ALL unique variants found within the individual sample.variant.db databases
Input:	Path where the sample.varaint.db database files are located
Output:	variants.db database

  ch-toolkit merge-batch-variants \
    --db-path variant_databases/ \
    --vdb database/variants.db \
    --batch-number 1

Output Variants to VCF

dump-variants
Goal:	Convert variants within variants.db into a VCF file for use in various annotation like VEP, PoN Pileup, etc.
Input:	variants.db database containing all unique variants that need to be converted into a VCF file
Output:	A VCF file containing all unique variants from variants.db

  ch-toolkit dump-variants \
    --vdb database/variants.db \
    --header-type simple \
    --batch-number 1

Importing VCF/Caller Specific Information for a Single Sample

import-sample-vcf
Goal:	Create individual sample.caller.db databases for each sample that will contain the caller specific information
Input:	Sample VCF file containing the information from the specific caller
Output:	sample.caller.db database

  ch-toolkit import-sample-vcf \
    --caller mutect \
    --input-vcf mutect.sample_name.vcf.gz \
    --cdb mutect_databases/mutect.sample_name.db \
    --batch-number 1

  ch-toolkit import-sample-vcf \
    --caller vardict \
    --input-vcf vardict.sample_name.vcf.gz \
    --cdb vardict_databases/vardict.sample_name.db \
    --batch-number 1

Create a Single Centralized Mutect and Vardict Caller Database from all Individual Sample Caller Databases

merge-batch-vcf
Goal:	Create a single mutect.db and vardict.db database that will contain ALL caller specific information found within the individual sample.caller.db databases
Input:	Path where the sample.caller.db database files are located
Output:	mutect.db database or vardict.db database

  ch-toolkit merge-batch-vcf \
    --db-path mutect_databases/ \
    --cdb database/mutect.db \
    --vdb database/variants.db \
    --sdb database/samples.db \
    --caller mutect \
    --batch-number 1	

  ch-toolkit merge-batch-vcf \
    --db-path mutect_databases/ \
    --cdb database/vardict.db \
    --vdb database/variants.db \
    --sdb database/samples.db \
    --caller vardict \
    --batch-number 1

After Annotating Variants Using VEP, Import VEP Information

import-vep
Goal:	Import annotation information produced from annotating variants from the dump-variants step using VEP
Input:	The resulting TSV file produced from running VEP using (--tab) mode
Output:	annotations.db database

  ch-toolkit import-vep \
    --adb database/annotations.db \
    --vdb database/variants.db \
    --vep VEP_annotated.tsv \
    --batch-number 1

Leveraging the Annotations from VEP, output Variants that are Potentially Putative Drivers

dump-annotations
Goal:	Export variants that are potentially putative drivers to be annotated by the custom AnnotatePD RScript
Input:	annotations.db database containing information about the variants that need to be converted into a CSV file
Output:	A CSV file containing all unique variants from annotations.db that will be annotated using AnnotatePD

  ch-toolkit dump-annotations \
    --adb database/annotations.db \
    --batch-number 1

After Annotating Variants Using AnnotatePD, Import AnnotatePD Information

import-annotate-pd
Goal:	Import annotation information produced from annotating variants from the dump-annotations step using AnnotatePD
Input:	The resulting CSV file produced from running AnnotatePD
Output:	annotations.db database

  ch-toolkit import-annotate-pd \
    --adb database/annotations.db \
    --pd annotatePD_results.csv \
    --batch-number 1

After Performing the PoN Pileup Workflow, Import Pileup Information

import-pon-pileup
Goal:	Import pileup information produced from running the PoN Pileup Workflow on the variants from the dump-variants step
Input:	The resulting PoN Pileup VCF file produced from the PoN Pileup Workflow
Output:	pileup.db database

  ch-toolkit import-pon-pileup \
    --vdb database/variants.db \
    --pdb database/pileup.db \
    --pon-pileup pon_pileup.vcf.gz \
    --batch-number 1

Calculate the Signal-to-Noise Ratio for All Variants

calculate-fishers-test
Goal:	Perform a Fisher's Exact Test comparing the proportion of variant alleles to reference alleles to the proportion of the same variant alleles to reference alleles found within the PoN Samples
Input:	The pileup information within the pileups.db database along with variant information found within mutect.db or vardict.db databases
Output:	mutect.db and vardict.db databases updated with a p-value indiciating the signifance of the detected variant signal relative to the expected noise for the same given location

  ch-toolkit calculate-fishers-test \
    --pdb database/pileup.db \
    --cdb database/mutect.db \
    --caller mutect \
    --batch-number 1

  ch-toolkit calculate-fishers-test \
    --pdb database/pileup.db \
    --cdb database/vardict.db \
    --caller vardict \
    --batch-number 1

Filter and Identify Putative Driver Variants

dump-ch
Goal:	Process through all information currently stored in the databases and detect CH variants with pathogenic support
Input:	mutect.db, vardict.db, and annotations.db databases
Output:	A CSV file containing all of the variants and all relevant information pertaining to said variants predicted to be pathogenic

  ch-toolkit dump-ch \
    --mcdb database/mutect.db \
    --vcdb database/vardict.db \
    --adb database/annotations.db

Additional Helper Functions

Split Database into Chromosomes for Processing

database-to-chromosome
Goal:	Divide the database into individual chromosome components. Useful for when the database is too large
Input:	mutect.db, vardict.db, annotations.db, variant.db, pileup.db databases
Output:	The original database used as input now split into all possible chromosomes from 1-22,X, and Y

  ch-toolkit database-to-chromosome \
    --db database/variants.db \
    --which_db variants \
    --batch-number 1 \
    --threads 4

Reducing Variant Databases to Exonic Regions

reduce-db
Goal:	Most CH mutations are only in the exonic regions, when processing, intronic regions may not be necessary
Input:	mutect.db or vardict.db and annotations.db databases
Output:	The original database used as input but only containing variants situated within the exonic regions of the genome

  ch-toolkit reduce-db \
    --cdb database/mutect.db \
    --caller mutect \
    --adb database/annotations.db \
    --threads 4

  ch-toolkit reduce-db \
    --cdb database/vardict.db \
    --caller vardict \
    --adb database/annotations.db \
    --threads 4