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noisyR: Enhancing biological signal in sequencing datasets by characterising random technical noise

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Moutsopoulos, Ilias  ORCID logo  https://orcid.org/0000-0003-4584-7849
Maischak, L 
Lauzikaite, E 
Vasquez Urbina, SA 
Williams, EC 

Abstract

High-throughput sequencing enables an unprecedented resolution in transcript quantification, at the cost of magnifying the impact of technical noise. The consistent reduction of random background noise to capture functionally meaningful biological signals is still challenging. Intrinsic sequencing variability introducing low-level expression variations can obscure patterns in downstream analyses. We introduce noisyR, a comprehensive noise filter to assess the variation in signal distribution and achieve an optimal information-consistency across replicates and samples; this selection also facilitates meaningful pattern recognition outside the background-noise range. noisyR is applicable to count matrices and sequencing data; it outputs samplespecific signal/noise thresholds and filtered expression matrices. We exemplify the effects of minimising technical noise on several datasets, across various sequencing assays: coding, non-coding RNAs and interactions, at bulk and single-cell level. An immediate consequence of filtering out noise is the convergence of predictions (differential-expression calls, enrichment analyses and inference of gene regulatory networks) across different approaches.

Description

Keywords

Algorithms, Animals, Arabidopsis, Computational Biology, Computer Simulation, Gene Expression Profiling, Gene Regulatory Networks, High-Throughput Nucleotide Sequencing, Humans, Mice, MicroRNAs, RNA, Messenger, RNA-Seq, Reproducibility of Results, Single-Cell Analysis

Journal Title

Nucleic Acids Research

Conference Name

Journal ISSN

0305-1048
1362-4962

Volume Title

Publisher

Oxford University Press (OUP)

Rights

All rights reserved
Sponsorship
MRC (MR/R50211X/1)
Medical Research Council (MC_PC_17230)