A combined approach with gene-wise normalization improves the analysis of RNA-seq data in human breast cancer subtypes.

ABSTRACT: Breast cancer (BC) is increasing in incidence and resistance to treatment worldwide. The challenges in limited therapeutic options and poor survival outcomes in BC subtypes persist because of its molecular heterogeneity and resistance to standard endocrine therapy. Recently, high throughput RNA sequencing (RNA-seq) has been used to identify biomarkers of disease progression and signaling pathways that could be amenable to specific therapies according to the BC subtype. However, there is no single generally accepted pipeline for the analysis of RNA-seq data in biomarker discovery due, in part, to the needs of simultaneously satisfying constraints of sensitivity and specificity. We proposed a combined approach using gene-wise normalization, UQ-pgQ2, followed by a Wald test from DESeq2. Our a

SUBMITTER: Li X 

PROVIDER: S-EPMC6082555 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature