Publication
Title
Transcriptomics in toxicogenomics, part II : preprocessing and differential expression analysis for high quality data
Author
Abstract
Preprocessing of transcriptomics data plays a pivotal role in the development of toxicogenomics-driven tools for chemical toxicity assessment. The generation and exploitation of large volumes of molecular profiles, following an appropriate experimental design, allows the employment of toxicogenomics (TGx) approaches for a thorough characterisation of the mechanism of action (MOA) of different compounds. To date, a plethora of data preprocessing methodologies have been suggested. However, in most cases, building the optimal analytical workflow is not straightforward. A careful selection of the right tools must be carried out, since it will affect the downstream analyses and modelling approaches. Transcriptomics data preprocessing spans across multiple steps such as quality check, filtering, normalization, batch effect detection and correction. Currently, there is a lack of standard guidelines for data preprocessing in the TGx field. Defining the optimal tools and procedures to be employed in the transcriptomics data preprocessing will lead to the generation of homogeneous and unbiased data, allowing the development of more reliable, robust and accurate predictive models. In this review, we outline methods for the preprocessing of three main transcriptomic technologies including microarray, bulk RNA-Sequencing (RNA-Seq), and single cell RNA-Sequencing (scRNA-Seq). Moreover, we discuss the most common methods for the identification of differentially expressed genes and to perform a functional enrichment analysis. This review is the second part of a three-article series on Transcriptomics in Toxicogenomics.
Language
English
Source (journal)
Nanomaterials
Publication
Basel : Mdpi , 2020
ISSN
2079-4991
DOI
10.3390/NANO10050903
Volume/pages
10 :5 (2020) , 21 p.
Article Reference
903
ISI
000540781800086
Pubmed ID
32397130
Note
Special issue from Nanoinformatics to Nanomaterials Risk Assessment and Governance
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Research group
Publication type
Subject
External links
Web of Science
Record
Identifier
Creation 07.10.2020
Last edited 26.11.2024
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