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Estimation of the strandness

In practice, with Illumina RNA-seq protocols you will most likely deal with either:

  • Unstranded RNAseq data

  • Stranded RNA-seq data produced with - kits and dUTP tagging (ISR)

This information should be provided with your FASTQ files, ask your sequencing facility!

If not, try to find it on the site where you downloaded the data or in the corresponding publication.

Another option is to estimate these parameters with a tool called Infer Experiment from the RSeQC tool suite. This tool takes the output of your mappings (BAM files), selects a subsample of your reads and compares their genome coordinates and strands with those of the reference gene model (from an annotation file).

Based on the strand of the genes, it can gauge whether sequencing is strand-specific, and if so, how reads are stranded.

Use of Infer Experiment tool

Convert GTF to BED12 tool to convert the GTF file to BED

  1. Go to your history STAR or HISAT2
  2. Select the tool Convert GTF to BED12
    1. GTF File to convert: Drosophila_melanogaster.BDGP6.95.gtf
  3. Execute

Infer Experiment tool to determine the library strandness

  1. In the same history STAR or HISAT2
  2. Select the tool Infer Experiment
    1. Input .bam file: mapped.bam files (outputs of RNA STAR or HISAT2 tools)
    2. Reference gene model : BED12 file (output of Convert GTF to BED12 tool)
    3. Number of reads sampled from SAM/BAM file (default = 200000): 200000
  3. Execute

Summarize results with MultiQC tool

  1. Select the tool MultiQC
  2. Which tool was used generate logs?
    • RSeQC
  3. RSeQC output (Type of RSeQC output?)
    • infer_experiment
  4. Select the 7 datasets of type Infer Experiment on ...
  5. Execute

Infer Experiment tool generates one file with information on:

  • Paired-end or single-end library
  • Fraction of reads failed to determine
  • 2 lines:
    • For single-end
      • Fraction of reads explained by “++,–” (SF in previous figure)
      • Fraction of reads explained by “+-,-+” (SR in previous figure)
    • For paired-end
      • Fraction of reads explained by “1++,1–,2+-,2-+” (SF in previous figure)
      • Fraction of reads explained by “1+-,1-+,2++,2–” (SR in previous figure)

If the two “Fraction of reads explained by” numbers are close to each other (i.e. a mix of SF and SR), we conclude that the library is not a strand-specific dataset (U in previous figure).

As it is sometimes quite difficult to find out which settings correspond to those of other programs, the following table might be helpful to identify the library type:

Library type Infer Experiment TopHat HISAT htseq-count featureCounts
Paired-End (PE) - SF 1++,1–,2+-,2-+ FR Second Strand Second Strand F/FR yes Forward (1)
PE - SR 1+-,1-+,2++,2– FR First Strand First Strand R/RF reverse Reverse (2)
Single-End (SE) - SF +,– FR Second Strand Second Strand F/FR yes Forward (1)
SE - SR +-,-+ FR First Strand First Strand R/RF reverse Reverse (2)
PE, SE - U undecided FR Unstranded default no Unstranded (0)