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A method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large dimensional trace. SpliceNet goes beyond differentially expressed genes and infers splicing isoform network changes between normal and diseased samples. It eases the sample size bottleneck; evaluations on simulated data and lung cancer-specific ERBB2 and MAPK signaling pathways, with varying number of samples, evince the merit in handling high exon to sample size ratio datasets.

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SpliceNet classification

SpliceNet specifications

Software type:
Package
Restrictions to use:
None
Programming languages:
R
Stability:
Stable
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:
Advanced

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