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UCL-BLIC/rnaseq_variant_calling Output

UCL-BLIC/rnaseq_variant_calling is a pipeline to call variants on RNAseq data. This document describes the output produced by the pipeline.

Most of the plots are taken from the MultiQC report, which summarises results at the end of the pipeline.

Pipeline overview

The pipeline is built using Nextflow and processes data using the following steps:

FastQC

FastQC gives general quality metrics about your reads. It provides information about the quality score distribution across your reads, the per base sequence content (%T/A/G/C). You get information about adapter contamination and other overrepresented sequences.

For further reading and documentation see the FastQC help.

NB: The FastQC plots displayed in the MultiQC report shows untrimmed reads. They may contain adapter sequence and potentially regions with low quality. To see how your reads look after trimming, look at the FastQC reports in the trim_galore directory.

Output directory: results/fastqc

  • sample_fastqc.html
    • FastQC report, containing quality metrics for your untrimmed raw fastq files
  • zips/sample_fastqc.zip
    • zip file containing the FastQC report, tab-delimited data file and plot images

TrimGalore

The pipeline uses TrimGalore for removal of adapter contamination and trimming of low quality regions. TrimGalore uses Cutadapt for adapter trimming and runs FastQC after it finishes.

MultiQC reports the percentage of bases removed by TrimGalore in the General Statistics table, along with a line plot showing where reads were trimmed.

Output directory: results/trim_galore

Contains FastQ files with quality and adapter trimmed reads for each sample, along with a log file describing the trimming.

  • sample_val_1.fq.gz, sample_val_2.fq.gz
    • Trimmed FastQ data, reads 1 and 2.
    • NB: Only saved if --saveTrimmed has been specified.
  • logs/sample_val_1.fq.gz_trimming_report.txt
    • Trimming report (describes which parameters that were used)
  • FastQC/sample_val_1_fastqc.zip
    • FastQC report for trimmed reads

Single-end data will have slightly different file names and only one FastQ file per sample.

STAR

STAR is a read aligner designed for RNA sequencing. STAR stands for Spliced Transcripts Alignment to a Reference, it produces results comparable to TopHat (the aligned previously used by NGI for RNA alignments) but is much faster.

The STAR section of the MultiQC report shows a bar plot with alignment rates: good samples should have most reads as Uniquely mapped and few Unmapped reads.

STAR

Output directory: results/STAR

  • Sample_Aligned.sortedByCoord.out.bam
    • The aligned BAM file
  • Sample_Log.final.out
    • The STAR alignment report, contains mapping results summary
  • Sample_Log.out and Sample_Log.progress.out
    • STAR log files, containing a lot of detailed information about the run. Typically only useful for debugging purposes.
  • Sample_SJ.out.tab
    • Filtered splice junctions detected in the mapping

Picard

Picard MarkDuplicates locates and tags duplicate reads in a BAM or SAM file, where duplicate reads are defined as originating from a single fragment of DNA. Duplicates can arise during sample preparation e.g. library construction using PCR.

The MarkDuplicates tool works by comparing sequences in the 5 prime positions of both reads and read-pairs in a SAM/BAM file. After duplicate reads are collected, the tool differentiates the primary and duplicate reads using an algorithm that ranks reads by the sums of their base-quality scores (default method). For more information visit the picard docs.

Output directory: results/markDuplicates

GATK

The pipeline uses the suggested GATK pipeline for [variant calling on RNAseq data] (https://software.broadinstitute.org/gatk/documentation/article.php?id=3891), and follows the following steps:

  • picard AddOrReplaceReadGroups: adding read group information
  • SplitNCigarReads: Next, we use a GATK tool called SplitNCigarReads developed specially for RNAseq, which splits reads into exon segments (getting rid of Ns but maintaining grouping information) and hard-clip any sequences overhanging into the intronic regions.
  • BaseRecalibrator: The GATK BaseRecalibrator detects systematic errors in base quality scores.
  • HaplotypeCaller: The GATK HaplotypeCaller calls germline SNPs, insertions and deletions via local re-assembly of haplotypes.
  • GenotypeGVCFs: The GATK GenotypeGVCFs performs joint genotyping on gVCF files produced by the GATK HaplotypeCaller.
  • VariantFiltration: Filter the resulting callset using hard filters

Output directory: results/variants

Annovar

annovar is a variant annotation and effect prediction tool. It annotates and predicts the effects of genetic variants (such as amino acid changes).

Output directory: results/variants

MultiQC

MultiQC is a visualisation tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in within the report data directory.

Output directory: results/MultiQC

  • Project_multiqc_report.html
    • MultiQC report - a standalone HTML file that can be viewed in your web browser
  • Project_multiqc_data/
    • Directory containing parsed statistics from the different tools used in the pipeline

For more information about how to use MultiQC reports, see http://multiqc.info