Current Challenges in the Bioinformatics of Single Cell Genomics

Single cell genomics is a rapidly growing field with many new techniques emerging in the past few years. However, few bioinformatics tools specific for single cell genomics analysis are available. Single cell DNA/RNA sequencing data usually have low genome coverage and high amplification bias, which...

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Main Authors:	Ning, Luwen, Liu, Geng, Li, Guibo, Hou, Yong, Tong, Yin, He, Jiankui
Format:	Online
Language:	English
Published:	Frontiers Media S.A. 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902584/

id	pubmed-3902584
recordtype	oai_dc
spelling	pubmed-39025842014-01-29 Current Challenges in the Bioinformatics of Single Cell Genomics Ning, Luwen Liu, Geng Li, Guibo Hou, Yong Tong, Yin He, Jiankui Oncology Single cell genomics is a rapidly growing field with many new techniques emerging in the past few years. However, few bioinformatics tools specific for single cell genomics analysis are available. Single cell DNA/RNA sequencing data usually have low genome coverage and high amplification bias, which makes bioinformatics analysis challenging. Many current bioinformatics tools developed for bulk cell sequencing do not work well with single cell sequencing data. Here, we summarize current challenges in the bioinformatics analysis of single cell genomic DNA sequencing and single cell transcriptomes. These challenges include calling copy number variations, identifying mutated genes in tumor samples, reconstructing cell lineages, recovering low abundant transcripts, and improving the accuracy of quantitative analysis of transcripts. Development in single cell genomics bioinformatics analysis will promote the application of this technology to basic biology and medical research. Frontiers Media S.A. 2014-01-27 /pmc/articles/PMC3902584/ /pubmed/24478987 http://dx.doi.org/10.3389/fonc.2014.00007 Text en Copyright © 2014 Ning, Liu, Li, Hou, Tong and He. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Ning, Luwen Liu, Geng Li, Guibo Hou, Yong Tong, Yin He, Jiankui
spellingShingle	Ning, Luwen Liu, Geng Li, Guibo Hou, Yong Tong, Yin He, Jiankui Current Challenges in the Bioinformatics of Single Cell Genomics
author_facet	Ning, Luwen Liu, Geng Li, Guibo Hou, Yong Tong, Yin He, Jiankui
author_sort	Ning, Luwen
title	Current Challenges in the Bioinformatics of Single Cell Genomics
title_short	Current Challenges in the Bioinformatics of Single Cell Genomics
title_full	Current Challenges in the Bioinformatics of Single Cell Genomics
title_fullStr	Current Challenges in the Bioinformatics of Single Cell Genomics
title_full_unstemmed	Current Challenges in the Bioinformatics of Single Cell Genomics
title_sort	current challenges in the bioinformatics of single cell genomics
description	Single cell genomics is a rapidly growing field with many new techniques emerging in the past few years. However, few bioinformatics tools specific for single cell genomics analysis are available. Single cell DNA/RNA sequencing data usually have low genome coverage and high amplification bias, which makes bioinformatics analysis challenging. Many current bioinformatics tools developed for bulk cell sequencing do not work well with single cell sequencing data. Here, we summarize current challenges in the bioinformatics analysis of single cell genomic DNA sequencing and single cell transcriptomes. These challenges include calling copy number variations, identifying mutated genes in tumor samples, reconstructing cell lineages, recovering low abundant transcripts, and improving the accuracy of quantitative analysis of transcripts. Development in single cell genomics bioinformatics analysis will promote the application of this technology to basic biology and medical research.
publisher	Frontiers Media S.A.
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902584/
_version_	1612051476843069440

Current Challenges in the Bioinformatics of Single Cell Genomics

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