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RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes

Recent advances in single-cell RNA sequencing technologies have made detection of transcripts in single cells possible. The level of resolution provided by these technologies can be used to study changes in transcript usage across cell populations and help investigate new biology. Here, we introduce...

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Detalles Bibliográficos
Autores principales: Stephenson, Maria, Nip, Ka Ming, HafezQorani, Saber, Gagalova, Kristina K, Yang, Chen, Warren, René L, Birol, Inanc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633890/
https://www.ncbi.nlm.nih.gov/pubmed/34859209
http://dx.doi.org/10.1093/nargab/lqab105
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author Stephenson, Maria
Nip, Ka Ming
HafezQorani, Saber
Gagalova, Kristina K
Yang, Chen
Warren, René L
Birol, Inanc
author_facet Stephenson, Maria
Nip, Ka Ming
HafezQorani, Saber
Gagalova, Kristina K
Yang, Chen
Warren, René L
Birol, Inanc
author_sort Stephenson, Maria
collection PubMed
description Recent advances in single-cell RNA sequencing technologies have made detection of transcripts in single cells possible. The level of resolution provided by these technologies can be used to study changes in transcript usage across cell populations and help investigate new biology. Here, we introduce RNA-Scoop, an interactive cell cluster and transcriptome visualization tool to analyze transcript usage across cell categories and clusters. The tool allows users to examine differential transcript expression across clusters and investigate how usage of specific transcript expression mechanisms varies across cell groups.
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spelling pubmed-86338902021-12-01 RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes Stephenson, Maria Nip, Ka Ming HafezQorani, Saber Gagalova, Kristina K Yang, Chen Warren, René L Birol, Inanc NAR Genom Bioinform APP Notes Recent advances in single-cell RNA sequencing technologies have made detection of transcripts in single cells possible. The level of resolution provided by these technologies can be used to study changes in transcript usage across cell populations and help investigate new biology. Here, we introduce RNA-Scoop, an interactive cell cluster and transcriptome visualization tool to analyze transcript usage across cell categories and clusters. The tool allows users to examine differential transcript expression across clusters and investigate how usage of specific transcript expression mechanisms varies across cell groups. Oxford University Press 2021-11-29 /pmc/articles/PMC8633890/ /pubmed/34859209 http://dx.doi.org/10.1093/nargab/lqab105 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (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 APP Notes
Stephenson, Maria
Nip, Ka Ming
HafezQorani, Saber
Gagalova, Kristina K
Yang, Chen
Warren, René L
Birol, Inanc
RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title_full RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title_fullStr RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title_full_unstemmed RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title_short RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes
title_sort rna-scoop: interactive visualization of transcripts in single-cell transcriptomes
topic APP Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633890/
https://www.ncbi.nlm.nih.gov/pubmed/34859209
http://dx.doi.org/10.1093/nargab/lqab105
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