bpucker / RNAseqQualCheck

script to assess the quality of RNAseq data sets

RNAseqQualCheck

This repository contains script to assess the quality of RNAseq data sets.

rRNA check

This script analyzes all reads in a FASTQ file. If multiple k-mers match an rRNA sequence, the read is classified as rRNA derived. This allows the comparison of different FASTQ files regarding the contamination of rRNA in different samples.

Usage
python3 rRNA_check.py --fastq <FILE> --rRNA <FILE> --out <DIR>

Mandatory:
--fastq    STR   FASTQ input file
--rRNA     STR   rRNA FASTA input file
--out      STR   Output folder

Optional:
--kmer     STR    Kmer size [21]
--cutoff   STR    Cutoff for read classification [3]

--fastq specifies a FASTQ input file that is analyzed. Each read is checked for the presence of rRNA sequence k-mers.

--rRNA specifies a FASTA input file that contains rRNA sequences of the species of interest. These sequences are processed to extract k-mers.

--out specifies an output folder. This folder will be created if it does not exist already.

--kmer specifies the size of k-mers used to screen reads for rRNA similarity. Default value is 21.

--cutoff specifies the number of k-mers that need to be detected in a read in order to classify it as rRNA read. Default is 3.

Example:

RNA-seq coverage across transcripts analysis

This script analyzes the coverage of RNA-seq reads across transcripts. The results allow conclusions about the quality of the processed sample.

Usage1
python3 read_distr_checker.py --bam <FILE> --gff <FILE> --out <DIR>

Usage2
python3 read_distr_checker.py --cov <FILE> --gff <FILE> --out <DIR>

Mandatory:
--bam        STR   BAM input file    |  --cov   STR    Coverage input file
--gff        STR   GFF input file
--out        STR   Output folder

Optional:
--sample     STR    Sample name
--samtools   STR    Path to samtools [samtools]
--bedtools   STR    Path to bedtools [bedtools]
--chunks     INT    Number of chunks [100]
--minexpcut  INT    Minimal coverage [100]

--bam specifies a BAM input file. This will be converted into a coverage file (COV) to analyze the distribution of reads across transcripts. This argument can also be used to provide a comma-separated list of files for automatic processing of large batches of files. --cov specifies a COV input file. This file is the basis to analyze the distribution of reads across transcripts. This argument can also be used to provide a comma-separated list of files for automatic processing of large batches of files. --gff specifies a GFF input file. This file is processed to identify the positions of exons that form an intron. --out specifies an output folder. If this folder does not exist, it will be created.

--sample specifies sample names. This argument can also be used to provide a comma-separated list of sample names for automatic processing of large batches of files. The length of this list should match the number of BAM/COV files provided. --samtools specifies the full path to samtools. Default: samtools. --bedtools specifies the full path to genomeCoverageBed. Default: genomeCoverageBed. --chunks specifies the number of chunks to create for each transcript when assessing the coverage. Default: 100. Only transcripts with at least this length will be considered for the analysis. --minexpcut specifies the minimal total number of sequenced basis. Only transcripts with at least this number of sequenced bases is considered for the analysis.

Dependencies

Python3 with standard modules is required to run this analysis. Plotting is based on matplotlib and seaborn.

sudo apt update
sudo apt install python3
sudo pip3 install matplotlib
sudo pip3 install seaborn

Samtools is needed to handle BAM files.

sudo apt update
sudo apt install samtools

Bedtools is needed to calculate coverage values.

sudo apt update
sudo apt install bedtools