Managing NGS differential expression uncertainty with fuzzy sets
Abstract
The application of high-performance Next-Generation Sequencing (NGS) technologies is widely used to characterize case-control comparison studies for RNA transcripts, such as mRNAs and small non-coding RNAs. The first step in the analy- sis strategies is mapping NGS reads against a reference database, and a critical issue is choosing how to deal with multiread problem. In this paper we present a novel ap- proach to represent and quantify read mapping ambiguities through the use of fuzzy sets and possibility theory. The aim of this work is to obtain a list of candidate differential expression events, ordered by significance, providing a description of the uncertainty of the results due to the multiread issue. A preliminary experiment on a case-control study of human endobronchial biopsies resulted in the identification of 9 genes with possible differential expression, four of them with an uncertain fold change. This result was con- firmed by FDR adjusted Fisher’s test, while the same data processed with DESeq2 did not provide significant differences between case and control.
Anno di pubblicazione
2016
ISSN
1611-3349
ISBN
9783319443317
Numero di citazioni Wos
Nessuna citazione
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Settori ERC
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Codici ASJC
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