how-are-we-stranded-here 1.0.1

Requirements

how_are_we_stranded_here requires the following packages be installed:

kallisto == 0.44.x

python >= 3.6.0

RSeQC

It also requires a transcriptome annotation (.fasta file - e.g. ensembl’s .cdna.fasta, or a prebuilt kallisto index), and a corresponding gtf.

Sometimes pseudoalignments will not work with newer versions of kallisto. If this is an issue, we suggest downgrading to 0.44.0.

Installation

pip install how_are_we_stranded_here

Usage

For basic usage, run check_strandedness with a gtf transcript annotation, transcripts fasta file and fastq read files from one sample.

check_strandedness --gtf Yeast.gtf --transcripts Yeast_cdna.fasta --reads_1 Sample_A_1.fq.gz --reads_2 Sample_A_2.fq.gz

Output

check_strandedness will print to console the results of infer_experiment.py (http://rseqc.sourceforge.net/#infer-experiment-py), along with an interpretation.

checking strandedness
Reading reference gene model stranded_test_WT_yeast_rep1_1_val_1_1/Saccharomyces_cerevisiae.R64-1-1.98.bed ... Done
Loading SAM/BAM file ...  Total 20000 usable reads were sampled
This is PairEnd Data
Fraction of reads failed to determine: 0.0595
Fraction of reads explained by "1++,1--,2+-,2-+": 0.0073 (0.8% of explainable reads)
Fraction of reads explained by "1+-,1-+,2++,2--": 0.9332 (99.2% of explainable reads)
Over 90% of reads explained by "1+-,1-+,2++,2--"
Data is likely RF/fr-firststrand

Any intermediate files are written to a folder in your current working directory derived from the name of the reads_1 file.

How it Works

check_strandedness.py runs a series of commands to check which direction reads align once mapped in transcripts.

It first creates a kallisto index (or uses a pre-made index) of your organisms transcriptome.

It then maps a small subset of reads (default 200000) to the transcriptome, and uses kallisto’s –genomebam argument to project pseudoalignments to genome sorted BAM file.

It finally runs RSeQC’s infer_experiment.py to check which direction reads from the first and second pairs are aligned in relation to the transcript strand, and provides output with the likely strandedness of your data.