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Python for gene expression
Genome biology shows substantial progress in its analytical and computational part in the last decades. Differential gene expression is one of many computationally intense areas; it is largely developed under R programming language. Here we explain possible reasons for such dominance of R in gene ex...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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F1000 Research Limited
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130758/ https://www.ncbi.nlm.nih.gov/pubmed/35646329 http://dx.doi.org/10.12688/f1000research.53842.2 |
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author | Bystrykh, Leonid |
author_facet | Bystrykh, Leonid |
author_sort | Bystrykh, Leonid |
collection | PubMed |
description | Genome biology shows substantial progress in its analytical and computational part in the last decades. Differential gene expression is one of many computationally intense areas; it is largely developed under R programming language. Here we explain possible reasons for such dominance of R in gene expression data. Next, we discuss the prospects for Python to become competitive in this area of research in coming years. We indicate that Python can be used already in a field of a single cell differential gene expression. We pinpoint still missing parts in Python and possibilities for improvement. |
format | Online Article Text |
id | pubmed-9130758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-91307582022-05-27 Python for gene expression Bystrykh, Leonid F1000Res Opinion Article Genome biology shows substantial progress in its analytical and computational part in the last decades. Differential gene expression is one of many computationally intense areas; it is largely developed under R programming language. Here we explain possible reasons for such dominance of R in gene expression data. Next, we discuss the prospects for Python to become competitive in this area of research in coming years. We indicate that Python can be used already in a field of a single cell differential gene expression. We pinpoint still missing parts in Python and possibilities for improvement. F1000 Research Limited 2022-06-23 /pmc/articles/PMC9130758/ /pubmed/35646329 http://dx.doi.org/10.12688/f1000research.53842.2 Text en Copyright: © 2022 Bystrykh L https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Opinion Article Bystrykh, Leonid Python for gene expression |
title | Python for gene expression |
title_full | Python for gene expression |
title_fullStr | Python for gene expression |
title_full_unstemmed | Python for gene expression |
title_short | Python for gene expression |
title_sort | python for gene expression |
topic | Opinion Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130758/ https://www.ncbi.nlm.nih.gov/pubmed/35646329 http://dx.doi.org/10.12688/f1000research.53842.2 |
work_keys_str_mv | AT bystrykhleonid pythonforgeneexpression |