Identification of novel ΔNp63α-regulated miRNAs using an optimized small RNA-Seq analysis pipeline.

ABSTRACT: Advances in high-throughput sequencing have enabled profiling of microRNAs (miRNAs), however, a consensus pipeline for sequencing of small RNAs has not been established. We built and optimized an analysis pipeline using Partek Flow, circumventing the need for analyzing data via scripting languages. Our analysis assessed the effect of alignment reference, normalization method, and statistical model choice on biological data. The pipeline was evaluated using sequencing data from HaCaT cells transfected with either a non-silencing control or siRNA against ΔNp63α, a p53 family member protein which is highly expressed in non-melanoma skin cancer and shown to regulate a number of miRNAs. We posit that 1) alignment and quantification to the miRBase reference provides the most robust quantitation

SUBMITTER: Sakaram S 

PROVIDER: S-EPMC6030203 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature