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Segmentation of genomic data through multivariate statistical approaches: comparative analysis

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Relation http://eprints.cmfri.org.in/16126/
https://epubs.icar.org.in/index.php/IJAgS/article/view/118040
https://doi.org/10.56093/ijas.v92i7.118040
 
Title Segmentation of genomic data through multivariate statistical approaches: comparative analysis
 
Creator Anjum, Arfa
Jaggi, Seema
Lall, Shwetank
Varghese, Eldho
Rai, Anil
Bhowmik, Arpan
Mishra, Dwijesh Chandra
 
Subject System analysis
 
Description Segmenting a series of measurements along a genome into regions with distinct characteristics is widely used to
identify functional components of a genome. The majority of the research on biological data segmentation focuses on the statistical problem of identifying break or change-points in a simulated scenario using a single variable. Despite the fact that various strategies for finding change-points in a multivariate setup through simulation are available, work on segmenting actual multivariate genomic data is limited. This is due to the fact that genomic data is huge in size and contains a lot of variation within it. Therefore, a study was carried out at the ICAR-Indian Agricultural Statistics Research Institute, New Delhi during 2021 to know the best multivariate statistical method to segment the sequences which may influence the properties or function of a sequence into homogeneous segments. This will reduce the volume of data and ease the analysis of these segments further to know the actual properties of these segments. The genomic data of Rice (Oryza sativa L.) was considered for the comparative analysis of several multivariate approaches and was found that agglomerative sequential clustering was the most acceptable due to its low computational cost and feasibility.
 
Publisher Indian Council of Agricultural Research
 
Date 2022
 
Type Article
PeerReviewed
 
Format text
 
Language en
 
Identifier http://eprints.cmfri.org.in/16126/1/Indian%20Journal%20of%20Agricultural%20Sciences_2022_Eldho%20Varghese.pdf
Anjum, Arfa and Jaggi, Seema and Lall, Shwetank and Varghese, Eldho and Rai, Anil and Bhowmik, Arpan and Mishra, Dwijesh Chandra (2022) Segmentation of genomic data through multivariate statistical approaches: comparative analysis. Indian Journal of Agricultural Sciences, 92 (7). pp. 92-96. ISSN 0019-5022