Goncalves, ANA;
Lever, M;
Russo, PST;
Gomes-Correia, B;
Urbanski, AH;
Pollara, G;
Noursadeghi, M;
... Nakaya, H; + view all
(2019)
Assessing the Impact of Sample Heterogeneity on Transcriptome Analysis of Human Diseases Using MDP Webtool.
Frontiers in Genetics
, 10
, Article 971. 10.3389/fgene.2019.00971.
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Abstract
Transcriptome analyses have increased our understanding of the molecular mechanisms underlying human diseases. Most approaches aim to identify significant genes by comparing their expression values between healthy subjects and a group of patients with a certain disease. Given that studies normally contain few samples, the heterogeneity among individuals caused by environmental factors or undetected illnesses can impact gene expression analyses. We present a systematic analysis of sample heterogeneity in a variety of gene expression studies relating to inflammatory and infectious diseases and show that novel immunological insights may arise once heterogeneity is addressed. The perturbation score of samples is quantified using nonperturbed subjects (i.e., healthy subjects) as a reference group. Such a score allows us to detect outlying samples and subgroups of diseased patients and even assess the molecular perturbation of single cells infected with viruses. We also show how removal of outlying samples can improve the “signal” of the disease and impact detection of differentially expressed genes. The method is made available via the mdp Bioconductor R package and as a user-friendly webtool, webMDP, available at http://mdp.sysbio.tools.
Type: | Article |
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Title: | Assessing the Impact of Sample Heterogeneity on Transcriptome Analysis of Human Diseases Using MDP Webtool |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3389/fgene.2019.00971 |
Publisher version: | https://doi.org/10.3389/fgene.2019.00971 |
Language: | English |
Additional information: | This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. http://creativecommons.org/licenses/by/4.0/ |
Keywords: | heterogeneity, transcriptome analysis, gene expression profiling, infectious diseases, inflammatory diseases |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Infection and Immunity |
URI: | https://discovery.ucl.ac.uk/id/eprint/10088295 |
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