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Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art

Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant...

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Detalles Bibliográficos
Autores principales: Seow, Justine Jia Wen, Wong, Regina Men Men, Pai, Rhea, Sharma, Ankur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264973/
https://www.ncbi.nlm.nih.gov/pubmed/32837038
http://dx.doi.org/10.1007/s41745-020-00178-1
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author Seow, Justine Jia Wen
Wong, Regina Men Men
Pai, Rhea
Sharma, Ankur
author_facet Seow, Justine Jia Wen
Wong, Regina Men Men
Pai, Rhea
Sharma, Ankur
author_sort Seow, Justine Jia Wen
collection PubMed
description Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has provided unprecedented insights into ITH and its implications in drug resistance and metastasis. As scRNA-seq technology grows and provides many new findings, new tools on different programming platforms are frequently generated. Here, we aim to provide a framework and guidelines for new entrants into the field of scRNA-seq. In this review, we discuss the current state-of-art of scRNA-seq analysis step-by-step including filtering, normalization and analysis. First, we discuss the brief history of experimental methods, followed by data processing and implications in precision oncology.
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spelling pubmed-72649732020-06-02 Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art Seow, Justine Jia Wen Wong, Regina Men Men Pai, Rhea Sharma, Ankur J Indian Inst Sci Review Article Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has provided unprecedented insights into ITH and its implications in drug resistance and metastasis. As scRNA-seq technology grows and provides many new findings, new tools on different programming platforms are frequently generated. Here, we aim to provide a framework and guidelines for new entrants into the field of scRNA-seq. In this review, we discuss the current state-of-art of scRNA-seq analysis step-by-step including filtering, normalization and analysis. First, we discuss the brief history of experimental methods, followed by data processing and implications in precision oncology. Springer India 2020-06-02 2020 /pmc/articles/PMC7264973/ /pubmed/32837038 http://dx.doi.org/10.1007/s41745-020-00178-1 Text en © The Author(s) 2020 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 Review Article
Seow, Justine Jia Wen
Wong, Regina Men Men
Pai, Rhea
Sharma, Ankur
Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title_full Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title_fullStr Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title_full_unstemmed Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title_short Single‐Cell RNA Sequencing for Precision Oncology: Current State-of-Art
title_sort single‐cell rna sequencing for precision oncology: current state-of-art
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7264973/
https://www.ncbi.nlm.nih.gov/pubmed/32837038
http://dx.doi.org/10.1007/s41745-020-00178-1
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