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DiffSplice | The genome-wide detection of differential splicing events with RNA-seq

Detects and visualizes of differential alternative transcription. DiffSplice is an ab initio method to detect alternative splicing isoforms that are differentially expressed under different conditions using high-throughput RNA-seq reads. This software directly localizes where differential splicing occurs, making it easier to identify exons involved in alternative transcription. It estimates the relative proportion of alternative transcription flows in every ASM and calculates the Jensen–Shannon divergence (JSD) to quantify the difference in transcription between samples.

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DiffSplice forum

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DiffSplice classification

DiffSplice specifications

Unique identifier:
OMICS_01330
Interface:
Command line interface
Input data:
RNA-seq alignment files.
Output data:
Alternative splicing modules (ASMs).
Operating system:
Unix/Linux, Mac OS
Version:
0.1.2
Requirements:
g++
Software type:
Application/Script, Package/Module
Restrictions to use:
None
Input format:
SAM
Output format:
GTF + TXT
Computer skills:
Advanced
Stability:
Beta
Maintained:
Yes

DiffSplice distribution

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DiffSplice support

Maintainer

  • Jinze Liu <>

Credits

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Publications

Institution(s)

Department of Computer Science, University of Kentucky, Lexington, KY, USA; UNC Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA ; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA ; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA ; Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Funding source(s)

Supported by US National Institutes of Health [R01-HG006272]; US National Science Foundation [EF-0850237], NSF Career award [IIS-1054631], National Institutes of Health grants [RC1-HL100108, AA017376, U24-CA143848 and 3U24-CA143848-02S1, R01-CA149569-03] and UNC University Cancer Research Fund.

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