brewerix-cli

Detect loss of imprinting or X-chromosome inactivation erosion from RNAseq data

Prerequisite

Software (must be available on PATH)

• GATK (>= 4.0.0)
• hisat2
• samtools

Knowledge-base

To run brewerix-cli you need to create a knowledge-base for your species of interest. The knowledge-base must be composed as follows:

• a BED file with the interesting regions
• the list of biallelic SNVs that lay on the potentially imprinted genes and sexual chromosomes
• the list of multi-allelic SNVs that lay on the potentially imprinted genes and sexual chromosomes (optional)
• the genome (with both genome dict and genome fa index '.fai')
• the genome indexed for hisat2

We built a wrapper to create the knowledge-base called brewerix-prepare-knowledgebase. Minimal requirements are

• the species of interest (must be available on ENSEMBL)
• a file with the list of chromosomes
• a file with the list of imprinted genes

General Workflow

This pipeline is able to generate a table of bi-allelic SNVs starting from FASTQ files.

In the following lines we summarize the major steps:

• collect fastqs
• generate the bams filtered by the region of interest
• Haplotype caller for multi-allelic SNVs (optional)
  • merge bi-allelic SNVs with the bi-allelic batch (optional)
• process with ASEReadCounted (GATK) on bi-allelic SNVs
• merge the sample in the global matrix
• annotation and additional filtering

The final output is a table that can be analyzed by brewerIX app.

Quick start

The simplest situation is to perform the analysis of single end samples
with the standard pipeline, i.e. using a pre-built set of bi-allelic SNVs.

The call should look like this one:

guess-LOI fqs snps-biallelic.vcf \
  genes-and-sex-regions.bed \
  genome.fa hisat2-index/genome *.fastq.gz