| RSeQC package 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. |
hg clone https://toolshed.g2.bx.psu.edu/repos/nilesh/rseqc
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| Name | Version | Type | |
|---|---|---|---|
| R | 3.0.3 | package | |
| numpy | 1.7.1 | package | |
| rseqc | 2.4 | package | |
| Name | Description | Version | Minimum Galaxy Version |
|---|---|---|---|
| estimates clipping profile of RNA-seq reads from BAM or SAM file | 2.4galaxy1 | any | |
| reads mapping statistics for a provided BAM or SAM file. | 2.4galaxy1 | any | |
| detects splice junctions from each subset and compares them to reference gene model | 2.4galaxy1 | any | |
| converts all types of RNA-seq data from .bam to .wig | 2.4galaxy1 | any | |
| determines reads duplication rate with sequence-based and mapping-based strategies | 2.4galaxy1 | any | |
| Read coverage over gene body. | 2.4galaxy2 | any | |
| calculates raw count and RPKM values for transcript at exon, intron, and mRNA level | 2.4galaxy1 | any | |
| compares detected splice junctions to reference gene model | 2.4galaxy1 | any | |
| determines Phred quality score | 2.4galaxy1 | any | |
| calculates raw count and RPKM values for transcript at exon, intron, and mRNA level | 2.4galaxy1 | any | |
| determines GC% and read count | 2.4galaxy1 | any | |
| Read coverage over gene body | 2.4galaxy1 | any | |
| calculates how mapped reads were distributed over genome feature | 2.4galaxy1 | any | |
| speculates how RNA-seq were configured | 2.4galaxy1 | any | |
| calculate the inner distance (or insert size) between two paired RNA reads | 2.4galaxy1 | any | |
| to check the nucleotide composition bias | 2.4galaxy1 | any | |