TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Krutik Patel; Sharmilla Chandrasegaran; Ian M. Clark; Carole J. Proctor; David A. Young; Daryl P. Shanley

doi:10.1093/bioinformatics/btab377

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Krutik Patel, Sharmilla Chandrasegaran, Ian M. Clark, Carole J. Proctor, David A. Young, Daryl P. Shanley

Research output: Contribution to journal › Article › peer-review

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Abstract

Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.

Original language	English
Pages (from-to)	3604–3609
Number of pages	6
Journal	Bioinformatics
Volume	37
Issue number	20
Early online date	16 May 2021
DOIs	https://doi.org/10.1093/bioinformatics/btab377
Publication status	Published - 15 Oct 2021

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10.1093/bioinformatics/btab377Licence: CC BY

Patel et al Bioinformatics 2021 in pressAccepted author manuscript, 1.34 MBLicence: CC BY

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@article{d6812f77971f4ea8883393a9eaa32d53,

title = "TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis",

abstract = "Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.",

author = "Krutik Patel and Sharmilla Chandrasegaran and Clark, {Ian M.} and Proctor, {Carole J.} and Young, {David A.} and Shanley, {Daryl P.}",

note = "Funding Information: K.P., I.M.C. and D.Y. are supported by the Dunhill Medical Trust [R476/ 0516]. D.P.S. is supported by Novo Nordisk Fonden Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging [NNF17OC0027812]. C.P., D.Y. and S.C. by the MRC and Versus Arthritis as part of the Medical Research Council Versus Arthritis Centre for Integrated Research into Musculoskeletal Ageing (CIMA) [MR/R502182/1].",

year = "2021",

month = oct,

day = "15",

doi = "10.1093/bioinformatics/btab377",

language = "English",

volume = "37",

pages = "3604–3609",

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T1 - TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

AU - Patel, Krutik

AU - Chandrasegaran, Sharmilla

AU - Clark, Ian M.

AU - Proctor, Carole J.

AU - Young, David A.

AU - Shanley, Daryl P.

N1 - Funding Information: K.P., I.M.C. and D.Y. are supported by the Dunhill Medical Trust [R476/ 0516]. D.P.S. is supported by Novo Nordisk Fonden Challenge Programme: Harnessing the Power of Big Data to Address the Societal Challenge of Aging [NNF17OC0027812]. C.P., D.Y. and S.C. by the MRC and Versus Arthritis as part of the Medical Research Council Versus Arthritis Centre for Integrated Research into Musculoskeletal Ageing (CIMA) [MR/R502182/1].

PY - 2021/10/15

Y1 - 2021/10/15

N2 - Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.

AB - Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.

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DO - 10.1093/bioinformatics/btab377

M3 - Article

VL - 37

SP - 3604

EP - 3609

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

IS - 20

ER -

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

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MicroRNAs are key mediators of cartilage destruction in osteoarthritis: in vivo, in vitro and in silico studies

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TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Abstract

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MicroRNAs are key mediators of cartilage destruction in osteoarthritis: in vivo, in vitro and in silico studies

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