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Single-cell RNA sequencing technologies and bioinformatics pipelines
Rapid progress in the development of next-generation sequencing (NGS) technologies in recent years has provided many valuable insights into complex biological systems, ranging from cancer genomics to diverse microbial communities. NGS-based technologies for genomics, transcriptomics, and epigenomics...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082860/ https://www.ncbi.nlm.nih.gov/pubmed/30089861 http://dx.doi.org/10.1038/s12276-018-0071-8 |
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author | Hwang, Byungjin Lee, Ji Hyun Bang, Duhee |
author_facet | Hwang, Byungjin Lee, Ji Hyun Bang, Duhee |
author_sort | Hwang, Byungjin |
collection | PubMed |
description | Rapid progress in the development of next-generation sequencing (NGS) technologies in recent years has provided many valuable insights into complex biological systems, ranging from cancer genomics to diverse microbial communities. NGS-based technologies for genomics, transcriptomics, and epigenomics are now increasingly focused on the characterization of individual cells. These single-cell analyses will allow researchers to uncover new and potentially unexpected biological discoveries relative to traditional profiling methods that assess bulk populations. Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in development. In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data. Further technical improvements at the level of molecular and cell biology and in available bioinformatics tools will greatly facilitate both the basic science and medical applications of these sequencing technologies. |
format | Online Article Text |
id | pubmed-6082860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-60828602018-08-17 Single-cell RNA sequencing technologies and bioinformatics pipelines Hwang, Byungjin Lee, Ji Hyun Bang, Duhee Exp Mol Med Review Article Rapid progress in the development of next-generation sequencing (NGS) technologies in recent years has provided many valuable insights into complex biological systems, ranging from cancer genomics to diverse microbial communities. NGS-based technologies for genomics, transcriptomics, and epigenomics are now increasingly focused on the characterization of individual cells. These single-cell analyses will allow researchers to uncover new and potentially unexpected biological discoveries relative to traditional profiling methods that assess bulk populations. Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in development. In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data. Further technical improvements at the level of molecular and cell biology and in available bioinformatics tools will greatly facilitate both the basic science and medical applications of these sequencing technologies. Nature Publishing Group UK 2018-08-07 /pmc/articles/PMC6082860/ /pubmed/30089861 http://dx.doi.org/10.1038/s12276-018-0071-8 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have permission under this license to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, http://creativecommons.org/licenses/by-nc-nd/4.0/. |
spellingShingle | Review Article Hwang, Byungjin Lee, Ji Hyun Bang, Duhee Single-cell RNA sequencing technologies and bioinformatics pipelines |
title | Single-cell RNA sequencing technologies and bioinformatics pipelines |
title_full | Single-cell RNA sequencing technologies and bioinformatics pipelines |
title_fullStr | Single-cell RNA sequencing technologies and bioinformatics pipelines |
title_full_unstemmed | Single-cell RNA sequencing technologies and bioinformatics pipelines |
title_short | Single-cell RNA sequencing technologies and bioinformatics pipelines |
title_sort | single-cell rna sequencing technologies and bioinformatics pipelines |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082860/ https://www.ncbi.nlm.nih.gov/pubmed/30089861 http://dx.doi.org/10.1038/s12276-018-0071-8 |
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