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miRkit: R framework analyzing miRNA PCR array data

OBJECTIVE: The characterization of microRNAs (miRNA) in recent years is an important advance in the field of gene regulation. To this end, several approaches for miRNA expression analysis and various bioinformatics tools have been developed over the last few years. It is a common practice to analyze...

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Autores principales: Tsagiopoulou, Maria, Togkousidis, Anastasis, Pechlivanis, Nikolaos, Maniou, Maria Christina, Batsali, Aristea, Matheakakis, Angelos, Pontikoglou, Charalampos, Psomopoulos, Fotis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8474725/
https://www.ncbi.nlm.nih.gov/pubmed/34565441
http://dx.doi.org/10.1186/s13104-021-05788-1
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author Tsagiopoulou, Maria
Togkousidis, Anastasis
Pechlivanis, Nikolaos
Maniou, Maria Christina
Batsali, Aristea
Matheakakis, Angelos
Pontikoglou, Charalampos
Psomopoulos, Fotis
author_facet Tsagiopoulou, Maria
Togkousidis, Anastasis
Pechlivanis, Nikolaos
Maniou, Maria Christina
Batsali, Aristea
Matheakakis, Angelos
Pontikoglou, Charalampos
Psomopoulos, Fotis
author_sort Tsagiopoulou, Maria
collection PubMed
description OBJECTIVE: The characterization of microRNAs (miRNA) in recent years is an important advance in the field of gene regulation. To this end, several approaches for miRNA expression analysis and various bioinformatics tools have been developed over the last few years. It is a common practice to analyze miRNA PCR Array data using the commercially available software, mostly due to its convenience and ease-of-use. RESULTS: In this work we present miRkit, an open source framework written in R, that allows for the comprehensive analysis of RT-PCR data, from the processing of raw data to a functional analysis of the produced results. The main goal of the proposed tool is to provide an assessment of the samples’ quality, perform data normalization by endogenous and exogenous miRNAs, and facilitate differential and functional enrichment analysis. The tool offers fast execution times with low memory usage, and is freely available under a ΜΙΤ license from https://bio.tools/mirkit. Overall, miRkit offers the full analysis from the raw RT-PCR data to functional analysis of targeted genes, and specifically designed to support the popular miScript miRNA PCR Array (Qiagen) technology.
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spelling pubmed-84747252021-09-28 miRkit: R framework analyzing miRNA PCR array data Tsagiopoulou, Maria Togkousidis, Anastasis Pechlivanis, Nikolaos Maniou, Maria Christina Batsali, Aristea Matheakakis, Angelos Pontikoglou, Charalampos Psomopoulos, Fotis BMC Res Notes Research Note OBJECTIVE: The characterization of microRNAs (miRNA) in recent years is an important advance in the field of gene regulation. To this end, several approaches for miRNA expression analysis and various bioinformatics tools have been developed over the last few years. It is a common practice to analyze miRNA PCR Array data using the commercially available software, mostly due to its convenience and ease-of-use. RESULTS: In this work we present miRkit, an open source framework written in R, that allows for the comprehensive analysis of RT-PCR data, from the processing of raw data to a functional analysis of the produced results. The main goal of the proposed tool is to provide an assessment of the samples’ quality, perform data normalization by endogenous and exogenous miRNAs, and facilitate differential and functional enrichment analysis. The tool offers fast execution times with low memory usage, and is freely available under a ΜΙΤ license from https://bio.tools/mirkit. Overall, miRkit offers the full analysis from the raw RT-PCR data to functional analysis of targeted genes, and specifically designed to support the popular miScript miRNA PCR Array (Qiagen) technology. BioMed Central 2021-09-26 /pmc/articles/PMC8474725/ /pubmed/34565441 http://dx.doi.org/10.1186/s13104-021-05788-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Note
Tsagiopoulou, Maria
Togkousidis, Anastasis
Pechlivanis, Nikolaos
Maniou, Maria Christina
Batsali, Aristea
Matheakakis, Angelos
Pontikoglou, Charalampos
Psomopoulos, Fotis
miRkit: R framework analyzing miRNA PCR array data
title miRkit: R framework analyzing miRNA PCR array data
title_full miRkit: R framework analyzing miRNA PCR array data
title_fullStr miRkit: R framework analyzing miRNA PCR array data
title_full_unstemmed miRkit: R framework analyzing miRNA PCR array data
title_short miRkit: R framework analyzing miRNA PCR array data
title_sort mirkit: r framework analyzing mirna pcr array data
topic Research Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8474725/
https://www.ncbi.nlm.nih.gov/pubmed/34565441
http://dx.doi.org/10.1186/s13104-021-05788-1
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