Notes on calling variants in RNA-seq data with GATK

• RNAseq includes reads mapped across splice junctions and is associated with high variability of coverage, so typical variant calling pipelines (for DNA) can lead to lots of false positives and negatives.
• GATK is currently the gold standard for calling variants in RNA-seq data. See a detailed description of their workflow here: ​https://gatkforums.broadinstitute.org/gatk/discussion/3892/the-gatk-best-practices-for-variant-calling-on-rnaseq-in-full-detail
• A main difference between calling variants in RNA vs DNA sequencing reads with GATK, is for RNA-seq data the STAR aligner is used to perform a 2-pass read mapping step, which was shown to have superior SNP sensitivity in a comparison of the most common mapping tools (​https://www.nature.com/nmeth/journal/v10/n12/full/nmeth.2722.html)

Using GATK to call variants from RNA-seq reads

This example pipeline starts with a single-end short-read fastq file (Reads_1.fq).

Note that GATK requires Java 1.7 (so you may need to adjust your path to point to that version, if an older version is the default).
For example, this can be added to ~/.bashrc:
export PATH=/usr/lib/jvm/java-7-openjdk-amd64/bin:$PATH