Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets

The X chromosome/autosome ratio has been widely used to profile XCU at the chromosomal level. However, this approach overlooks features of inside genes. Here, we present a computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing da...

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Detalles Bibliográficos
Autores principales: Yang, Qianying, Lyu, Qingji, Tian, Jianhui, An, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628899/
https://www.ncbi.nlm.nih.gov/pubmed/37897732
http://dx.doi.org/10.1016/j.xpro.2023.102680
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author Yang, Qianying
Lyu, Qingji
Tian, Jianhui
An, Lei
author_facet Yang, Qianying
Lyu, Qingji
Tian, Jianhui
An, Lei
author_sort Yang, Qianying
collection PubMed
description The X chromosome/autosome ratio has been widely used to profile XCU at the chromosomal level. However, this approach overlooks features of inside genes. Here, we present a computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets. We describe steps for selecting data, preparing software, processing data, and data analysis. This protocol quantifies the contribution value and contribution increment of each X-linked gene to XCU. For complete details on the use and execution of this protocol, please refer to Lyu et al. (2022).(1)
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spelling pubmed-106288992023-11-08 Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets Yang, Qianying Lyu, Qingji Tian, Jianhui An, Lei STAR Protoc Protocol The X chromosome/autosome ratio has been widely used to profile XCU at the chromosomal level. However, this approach overlooks features of inside genes. Here, we present a computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets. We describe steps for selecting data, preparing software, processing data, and data analysis. This protocol quantifies the contribution value and contribution increment of each X-linked gene to XCU. For complete details on the use and execution of this protocol, please refer to Lyu et al. (2022).(1) Elsevier 2023-10-27 /pmc/articles/PMC10628899/ /pubmed/37897732 http://dx.doi.org/10.1016/j.xpro.2023.102680 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Yang, Qianying
Lyu, Qingji
Tian, Jianhui
An, Lei
Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title_full Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title_fullStr Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title_full_unstemmed Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title_short Computational protocol for the identification of X-linked genes contributing to X chromosome upregulation from RNA-sequencing datasets
title_sort computational protocol for the identification of x-linked genes contributing to x chromosome upregulation from rna-sequencing datasets
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10628899/
https://www.ncbi.nlm.nih.gov/pubmed/37897732
http://dx.doi.org/10.1016/j.xpro.2023.102680
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