Tool:DNMF: Gene Ranking and differential expression analysis of RNA-Seq Data
Entering edit mode
6.1 years ago
Zhilong Jia ★ 2.0k

Here is a new tool for Gene Ranking and differential expression analysis of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization (DNMF).

1. What can DNMF do?

Gene ranks of RNA-seq for gene set enrichment analysis (GSEA) due to there are no built-in ranking methods for RNA-seq data. Or other tools requiring gene ranks. Additionally, differential expression analysis of RNA-Seq Data

2. Why DNMF?

Please read Jia Z, Zhang X, Guan N, Bo X, Barnes MR, Luo Z (2015) Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization. PLoS ONE 10(9): e0137782. doi:10.1371/journal.pone.0137782

3. How it works?

There are two types of samples, A and B, in the matrix V, each with four replicates. Via DNMF, two matrices, Wand H, are produced. The matrix H possesses the same column number as matrix V, while the matrix Wpossesses the same row number as matrix V. To explain it biologically, the row of H could be viewed as the metagenes (the up-regulated or down-regulated gene sets), while the column of W represents the weight of each gene in the metagenes. The two metagenes in matrix H, represent the up-regulated genes and down-regulated genes respectively. Due to the correspondence between columns of W and rows of H, it is possible to identify which metagenes are combined with the up-regulated or down-regulated gene sets in matrix W. Consequently, it is easy to obtain the rank of genes by subtraction between the weights of the two metagenes in matrix W

4. Code and bug reports

Thank you.

DNMF RNA-Seq gene ranking NMF gsea Tool • 3.4k views

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