Splicing Isoform Specific Differential Network Inference from RNA-Seq data


Recent studies demonstrated the merits of exon-level RNA-Seq data in profiling splice variants and constructing gene networks. However, the large number of exons versus small sample size limits their practical application. The method, SpliceNet goes beyond differentially expressed genes and abstracts isoform specific co-expression networks from exon-level RNA-Seq data using Large Dimensional Trace. It provides a more comprehensive picture to our understanding of complex diseases by inferring networks rewiring between normal and cancer/diseased samples at isoform resolution. It can be applied to any exon level RNA-Seq data and exon array data. Furthermore, by computing intra-genic isoform dependencies, SpliceNet can also infer isoform mediated auto regulatory dependencies.

SpliceNet Software

An R package implementing the method, SpliceNet can be downloaded here

Data preparation


This work was supported by the Research Grants Council (781511M) of Hong Kong and National Natural Science Foundation of China (91229105).


*Correspondence should be addressed to Junwen Wang
(Tel: +852 2819 2809; Fax: +852 2855 1254)
junwen@hku.hk ).
(Office: L3-80, Laboratory Block, 21 Sassoon Road, Hong Kong).