SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples

@article{Yalamanchili2014SpliceNetRS,
  title={SpliceNet: recovering splicing isoform-specific differential gene networks from RNA-Seq data of normal and diseased samples},
  author={Hari Krishna Yalamanchili and Zhaoyuan Li and Panwen Wang and Maria Pik Wong and Jianfeng Yao and Junwen Wang},
  journal={Nucleic Acids Research},
  year={2014},
  volume={42},
  pages={e121 - e121}
}
Conventionally, overall gene expressions from microarrays are used to infer gene networks, but it is challenging to account splicing isoforms. High-throughput RNA Sequencing has made splice variant profiling practical. However, its true merit in quantifying splicing isoforms and isoform-specific exon expressions is not well explored in inferring gene networks. This study demonstrates SpliceNet, a method to infer isoform-specific co-expression networks from exon-level RNA-Seq data, using large… 

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