Cargando…

Linking co-expression modules with phenotypes

The method for quantifying the association between co-expression module and clinical trait of interest requires application of dimensionality reduction to summaries modules as one dimensional (1D) vector. However, these methods are often linked with information loss. The amount of information lost d...

Descripción completa

Detalles Bibliográficos
Autores principales: Kumar, Rakesh, Ojha, Krishna Kumar, Yadav, Harlokesh Narayan, Singh, Vijay Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997497/
https://www.ncbi.nlm.nih.gov/pubmed/36909689
http://dx.doi.org/10.6026/97320630018438
_version_ 1784903267890757632
author Kumar, Rakesh
Ojha, Krishna Kumar
Yadav, Harlokesh Narayan
Singh, Vijay Kumar
author_facet Kumar, Rakesh
Ojha, Krishna Kumar
Yadav, Harlokesh Narayan
Singh, Vijay Kumar
author_sort Kumar, Rakesh
collection PubMed
description The method for quantifying the association between co-expression module and clinical trait of interest requires application of dimensionality reduction to summaries modules as one dimensional (1D) vector. However, these methods are often linked with information loss. The amount of information lost depends upon the percentage of variance captured by the reduced 1D vector. Therefore, it is of interest to describe a method using analysis of rank (AOR) to assess the association between module and clinical trait of interest. This method works with clinical traits represented as binary class labels and can be adopted for clinical traits measured in continuous scale by dividing samples in two groups around median value. Application of the AOR method on test data for muscle gene expression profiles identifies modules significantly associated with diabetes status.
format Online
Article
Text
id pubmed-9997497
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Biomedical Informatics
record_format MEDLINE/PubMed
spelling pubmed-99974972023-03-10 Linking co-expression modules with phenotypes Kumar, Rakesh Ojha, Krishna Kumar Yadav, Harlokesh Narayan Singh, Vijay Kumar Bioinformation Research Article The method for quantifying the association between co-expression module and clinical trait of interest requires application of dimensionality reduction to summaries modules as one dimensional (1D) vector. However, these methods are often linked with information loss. The amount of information lost depends upon the percentage of variance captured by the reduced 1D vector. Therefore, it is of interest to describe a method using analysis of rank (AOR) to assess the association between module and clinical trait of interest. This method works with clinical traits represented as binary class labels and can be adopted for clinical traits measured in continuous scale by dividing samples in two groups around median value. Application of the AOR method on test data for muscle gene expression profiles identifies modules significantly associated with diabetes status. Biomedical Informatics 2022-04-30 /pmc/articles/PMC9997497/ /pubmed/36909689 http://dx.doi.org/10.6026/97320630018438 Text en © 2022 Biomedical Informatics https://creativecommons.org/licenses/by/3.0/This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
spellingShingle Research Article
Kumar, Rakesh
Ojha, Krishna Kumar
Yadav, Harlokesh Narayan
Singh, Vijay Kumar
Linking co-expression modules with phenotypes
title Linking co-expression modules with phenotypes
title_full Linking co-expression modules with phenotypes
title_fullStr Linking co-expression modules with phenotypes
title_full_unstemmed Linking co-expression modules with phenotypes
title_short Linking co-expression modules with phenotypes
title_sort linking co-expression modules with phenotypes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997497/
https://www.ncbi.nlm.nih.gov/pubmed/36909689
http://dx.doi.org/10.6026/97320630018438
work_keys_str_mv AT kumarrakesh linkingcoexpressionmoduleswithphenotypes
AT ojhakrishnakumar linkingcoexpressionmoduleswithphenotypes
AT yadavharlokeshnarayan linkingcoexpressionmoduleswithphenotypes
AT singhvijaykumar linkingcoexpressionmoduleswithphenotypes