DSGseq statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.


Citations per year

Citations chart

Popular tool citations

chevron_left Differential expression Normalization Alternative splicing events identification Known transcript quantification chevron_right
Popular tools chart

Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

DSGseq specifications


Unique identifier OMICS_01331
Name DSGseq
Software type Toolkit/Suite
Interface Command line interface
Restrictions to use None
Input data Read count
Output data Differences in the relative abundance of the isoforms of each gene in the annotation
Biological technology Illumina, Life Technologies, Roche
Operating system Unix/Linux, Mac OS, Windows
Programming languages C, R
Computer skills Advanced
Version 0.1.0
Stability Beta
Maintained Yes



Add your version


  • person_outline Zhiyi Qin <>
  • person_outline Weichen Wang <>

Publication for DSGseq

DSGseq in publications

PMCID: 5294840
PMID: 28184252
DOI: 10.1186/s13040-017-0125-9

[…] probability adjusted to gene length. gsva estimates variation of pathway activity over a sample population and it is able to detect subtle changes of gene expression in the pathway. seqgsea adopts dsgseq [] and deseq [] for gene level test and uses the gsea method [] for functional enrichment analysis. camera [] estimates the inter-gene correlation and accordingly adjusts the gene set test […]

PMCID: 4728800
PMID: 26813401
DOI: 10.1186/s13059-016-0881-8

[…] of the genes between the compared samples. this approach is based on the premise that differences in isoform expression can be tracked in the signals of exons and their junctions. dexseq [] and dsgseq [] adopt a similar idea to detect differentially spliced genes by testing for significant differences in read counts on exons (and junctions) of the genes. rmats detects differential usage […]

PMCID: 4271460
PMID: 25511303
DOI: 10.1186/s12859-014-0364-4

[…] based on the classification nomenclature defined by pachter in []. we selected eight methods and evaluated them based on simulated and real data. six of them are from count-based models: dexseq [], dsgseq [], splicingcompass [], mats [], rdiff-parametric [] and seqgsea []. the remaining two, cufflinks [] and diffsplice [], use isoform resolution models. a brief overview of the eight methods […]

To access a full list of publications, you will need to upgrade to our premium service.

DSGseq institution(s)
MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing, China

DSGseq reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review DSGseq