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Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data

Transcription factor binding to a gene regulatory region induces or represses its expression. Binding and expression target analysis (BETA) integrates the binding and gene expression data to predict this function. First, the regulatory potential of the factor is modeled based on the distance of its...

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Autores principales: Ahmed, Mahmoud, Kim, Deok Ryong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592348/
https://www.ncbi.nlm.nih.gov/pubmed/37876906
http://dx.doi.org/10.7717/peerj.16318
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author Ahmed, Mahmoud
Kim, Deok Ryong
author_facet Ahmed, Mahmoud
Kim, Deok Ryong
author_sort Ahmed, Mahmoud
collection PubMed
description Transcription factor binding to a gene regulatory region induces or represses its expression. Binding and expression target analysis (BETA) integrates the binding and gene expression data to predict this function. First, the regulatory potential of the factor is modeled based on the distance of its binding sites from the transcription start sites in a decay function. Then the differential expression statistics from an experiment where this factor was perturbed represent the binding effect. The rank product of the two values is employed to order in importance. This algorithm was originally implemented in Python. We reimplemented the algorithm in R to take advantage of existing data structures and other tools for downstream analyses. Here, we attempted to replicate the findings in the original BETA paper. We applied the new implementation to the same datasets using default and varying inputs and cutoffs. We successfully replicated the original results. Moreover, we showed that the method was appropriately influenced by varying the input and was robust to choices of cutoffs in statistical testing.
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spelling pubmed-105923482023-10-24 Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data Ahmed, Mahmoud Kim, Deok Ryong PeerJ Bioinformatics Transcription factor binding to a gene regulatory region induces or represses its expression. Binding and expression target analysis (BETA) integrates the binding and gene expression data to predict this function. First, the regulatory potential of the factor is modeled based on the distance of its binding sites from the transcription start sites in a decay function. Then the differential expression statistics from an experiment where this factor was perturbed represent the binding effect. The rank product of the two values is employed to order in importance. This algorithm was originally implemented in Python. We reimplemented the algorithm in R to take advantage of existing data structures and other tools for downstream analyses. Here, we attempted to replicate the findings in the original BETA paper. We applied the new implementation to the same datasets using default and varying inputs and cutoffs. We successfully replicated the original results. Moreover, we showed that the method was appropriately influenced by varying the input and was robust to choices of cutoffs in statistical testing. PeerJ Inc. 2023-10-20 /pmc/articles/PMC10592348/ /pubmed/37876906 http://dx.doi.org/10.7717/peerj.16318 Text en © 2023 Ahmed and Kim https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Ahmed, Mahmoud
Kim, Deok Ryong
Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title_full Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title_fullStr Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title_full_unstemmed Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title_short Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data
title_sort validating a re-implementation of an algorithm to integrate transcriptome and chip-seq data
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10592348/
https://www.ncbi.nlm.nih.gov/pubmed/37876906
http://dx.doi.org/10.7717/peerj.16318
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