RLeave: an in silico cross-validation protocol for transcript differential expression analysis

Background and Objective: The massive parallel sequencing technology facilitates new discoveries in terms of transcript differential analysis; however, all the new findings must be validated, since the diversity of transcript expression may impair the identification of the most relevant ones. Method...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2020-12
Main Authors: Silva, Matheus Costa e, Lucena-Silva, Norma, Juliana Doblas Massaro, Donadi, Eduardo Antônio
Format: Article
Language:English
Subjects:
Algorithms
Decision trees
Diabetes mellitus
Leukemia
Ribonucleic acid
RNA
Sequences
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background and Objective: The massive parallel sequencing technology facilitates new discoveries in terms of transcript differential analysis; however, all the new findings must be validated, since the diversity of transcript expression may impair the identification of the most relevant ones. Methods: The proposed RLeave algorithm (implemented in the R environment) utilizes a combination of conventional analysis (classic edgeR) together with other mathematical methods (Leave-one-out sample technique and Decision Trees validation) to identify more relevant candidates to be in vitro or in silico validated. Results: The RLeave protocol was tested using miRNome expression analysis of two sample groups (diabetes mellitus and acute lymphoblastic leukemia), and both had their most important differentially expressed miRNA confirmed by RT-qPCR. Conclusion: This protocol is applicable in RNA-SEQ research, highlighting the most relevant transcripts for in silico and/or in vitro validation.
ISSN:2331-8422
DOI:10.48550/arxiv.2012.05421