Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays

The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell’s ability to reproduc...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Fangfei, Tarkington, Jason, Sherlock, Gavin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10276102/
https://www.ncbi.nlm.nih.gov/pubmed/36877292
http://dx.doi.org/10.1007/s00239-023-10098-0
_version_ 1785060005859295232
author Li, Fangfei
Tarkington, Jason
Sherlock, Gavin
author_facet Li, Fangfei
Tarkington, Jason
Sherlock, Gavin
author_sort Li, Fangfei
collection PubMed
description The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell’s ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.
format Online
Article
Text
id pubmed-10276102
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-102761022023-06-18 Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays Li, Fangfei Tarkington, Jason Sherlock, Gavin J Mol Evol Original Article The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell’s ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays. Springer US 2023-03-06 2023 /pmc/articles/PMC10276102/ /pubmed/36877292 http://dx.doi.org/10.1007/s00239-023-10098-0 Text en © The Author(s) 2023 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/) .
spellingShingle Original Article
Li, Fangfei
Tarkington, Jason
Sherlock, Gavin
Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title_full Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title_fullStr Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title_full_unstemmed Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title_short Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays
title_sort fit-seq2.0: an improved software for high-throughput fitness measurements using pooled competition assays
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10276102/
https://www.ncbi.nlm.nih.gov/pubmed/36877292
http://dx.doi.org/10.1007/s00239-023-10098-0
work_keys_str_mv AT lifangfei fitseq20animprovedsoftwareforhighthroughputfitnessmeasurementsusingpooledcompetitionassays
AT tarkingtonjason fitseq20animprovedsoftwareforhighthroughputfitnessmeasurementsusingpooledcompetitionassays
AT sherlockgavin fitseq20animprovedsoftwareforhighthroughputfitnessmeasurementsusingpooledcompetitionassays

Ejemplares similares