Identifier: TL_73aadb.49


Provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. Some basic modules quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while RNA-seq specific modules evaluate sequencing saturation, mapped reads distribution, coverage uniformity, strand specificity, transcript level RNA integrity etc.


  • rseqc read_distribution

    The tool calculates the fraction of reads mapped to coding exons, 5'-UTR exons, 3'-UTR exons, introns and intergenic regions based on the gene models provided

  • rseqc read_quality

    make read quality histogram

  • rseqc junction_saturation

    check if current sequencing depth is deep enough to perform alternative splicing analyses

  • rseqc infer_experiment

    This program is used to guess how RNA-seq sequencing were configured, particulary how reads were stranded for strand-specific RNA-seq data, through comparing the strandness of reads with the standness of transcripts

  • rseqc bam_stat

    This tool can be used to check the mapping statistics of reads - number of uniquely mapped reads, number reads mapped over a splice junction, number of reads mapped in proper pairs

  • rseqc junction_annotation

    For a given alignment file (-i) in BAM or SAM format and a reference gene model (-r) in BED format, this program will compare detected splice junctions to reference gene model. splicing annotation is performed in two levels - splice event level and splice junction level.

  • rseqc FPKM_count

    Calculate raw read count, FPM (fragment per million) and FPKM (fragment per million mapped reads per kilobase exon) for each gene in BED file. Note SAM file is not supported.

  • rseqc geneBody_coverage

    This tool scales all transcripts to 100nt and calculates the number of reads covering each nucleotide position.