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BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R
MOTIVATION: We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Cust...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388021/ https://www.ncbi.nlm.nih.gov/pubmed/33624743 http://dx.doi.org/10.1093/bioinformatics/btab121 |
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author | Rinchai, Darawan Roelands, Jessica Toufiq, Mohammed Hendrickx, Wouter Altman, Matthew C Bedognetti, Davide Chaussabel, Damien |
author_facet | Rinchai, Darawan Roelands, Jessica Toufiq, Mohammed Hendrickx, Wouter Altman, Matthew C Bedognetti, Davide Chaussabel, Damien |
author_sort | Rinchai, Darawan |
collection | PubMed |
description | MOTIVATION: We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. RESULTS: We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. AVAILABILITY AND IMPLEMENTATION: The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8388021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-83880212021-08-26 BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R Rinchai, Darawan Roelands, Jessica Toufiq, Mohammed Hendrickx, Wouter Altman, Matthew C Bedognetti, Davide Chaussabel, Damien Bioinformatics Original Papers MOTIVATION: We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. RESULTS: We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. AVAILABILITY AND IMPLEMENTATION: The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-02-24 /pmc/articles/PMC8388021/ /pubmed/33624743 http://dx.doi.org/10.1093/bioinformatics/btab121 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Rinchai, Darawan Roelands, Jessica Toufiq, Mohammed Hendrickx, Wouter Altman, Matthew C Bedognetti, Davide Chaussabel, Damien BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title | BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title_full | BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title_fullStr | BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title_full_unstemmed | BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title_short | BloodGen3Module: blood transcriptional module repertoire analysis and visualization using R |
title_sort | bloodgen3module: blood transcriptional module repertoire analysis and visualization using r |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388021/ https://www.ncbi.nlm.nih.gov/pubmed/33624743 http://dx.doi.org/10.1093/bioinformatics/btab121 |
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