File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1038/srep00055
- Scopus: eid_2-s2.0-84857232194
- PMID: 22355574
- WOS: WOS:000296050700001
- Find via
Supplementary
-
Bookmarks:
- CiteULike: 10
- Citations:
- Appears in Collections:
Article: Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions
Title | Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions | ||||||
---|---|---|---|---|---|---|---|
Authors | |||||||
Keywords | Computational biology and bioinformatics Gene regulation Cancer genomics | ||||||
Issue Date | 2011 | ||||||
Publisher | Nature Publishing Group. The Journal's web site is located at http://www.nature.com/srep/index.html | ||||||
Citation | Scientific Reports, 2011, v. 1, article no. 55 How to Cite? | ||||||
Abstract | The rapid development of next generation sequencing (NGS) technology provides a new chance to extend the scale and resolution of genomic research. How to efficiently map millions of short reads to the reference genome and how to make accurate SNP calls are two major challenges in taking full advantage of NGS. In this article, we reviewed the current software tools for mapping and SNP calling, and evaluated their performance on samples from The Cancer Genome Atlas (TCGA) project. We found that BWA and Bowtie are better than the other alignment tools in comprehensive performance for Illumina platform, while NovoalignCS showed the best overall performance for SOLiD. Furthermore, we showed that next-generation sequencing platform has significantly lower coverage and poorer SNP-calling performance in the CpG islands, promoter and 5'-UTR regions of the genome. NGS experiments targeting for these regions should have higher sequencing depth than the normal genomic region. | ||||||
Persistent Identifier | http://hdl.handle.net/10722/138955 | ||||||
ISSN | 2023 Impact Factor: 3.8 2023 SCImago Journal Rankings: 0.900 | ||||||
PubMed Central ID | |||||||
ISI Accession Number ID |
Funding Information: Financial support was provided by Grants from the Research Grants Council (781511M, 778609M, N_HKU752/10) and Food and Health Bureau (10091262) of Hong Kong. | ||||||
References | |||||||
Grants |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, W | en_HK |
dc.contributor.author | Zhi, W | en_HK |
dc.contributor.author | Lam, TW | en_HK |
dc.contributor.author | Wang, JJ | en_HK |
dc.date.accessioned | 2011-09-23T05:43:05Z | - |
dc.date.available | 2011-09-23T05:43:05Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Scientific Reports, 2011, v. 1, article no. 55 | en_HK |
dc.identifier.issn | 2045-2322 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/138955 | - |
dc.description.abstract | The rapid development of next generation sequencing (NGS) technology provides a new chance to extend the scale and resolution of genomic research. How to efficiently map millions of short reads to the reference genome and how to make accurate SNP calls are two major challenges in taking full advantage of NGS. In this article, we reviewed the current software tools for mapping and SNP calling, and evaluated their performance on samples from The Cancer Genome Atlas (TCGA) project. We found that BWA and Bowtie are better than the other alignment tools in comprehensive performance for Illumina platform, while NovoalignCS showed the best overall performance for SOLiD. Furthermore, we showed that next-generation sequencing platform has significantly lower coverage and poorer SNP-calling performance in the CpG islands, promoter and 5'-UTR regions of the genome. NGS experiments targeting for these regions should have higher sequencing depth than the normal genomic region. | en_HK |
dc.language | eng | en_US |
dc.publisher | Nature Publishing Group. The Journal's web site is located at http://www.nature.com/srep/index.html | - |
dc.relation.ispartof | Scientific Reports | en_HK |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Computational biology and bioinformatics | - |
dc.subject | Gene regulation | - |
dc.subject | Cancer genomics | - |
dc.title | Next generation sequencing has lower sequence coverage and poorer SNP-detection capability in the regulatory regions | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Lam, TW: hresltk@hkucc.hku.hk | en_HK |
dc.identifier.email | Wang, JJ: junwen@hku.hk | en_HK |
dc.identifier.authority | Lam, TW=rp00135 | en_HK |
dc.identifier.authority | Wang, JJ=rp00280 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1038/srep00055 | en_HK |
dc.identifier.pmid | 22355574 | - |
dc.identifier.pmcid | PMC3216542 | - |
dc.identifier.scopus | eid_2-s2.0-84857232194 | en_HK |
dc.identifier.hkuros | 192078 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-84857232194&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 1, article no. 55 | en_HK |
dc.identifier.eissn | 2045-2322 | - |
dc.identifier.isi | WOS:000296050700001 | - |
dc.publisher.place | United Kingdom | - |
dc.relation.project | A Novel Hidden Markov Model to Predict microRNAs and their Targets Simultaneously and its Application to the Epstein-Barr virus | - |
dc.identifier.scopusauthorid | Wang, J=8950599500 | en_HK |
dc.identifier.scopusauthorid | Lam, TW=7202523165 | en_HK |
dc.identifier.scopusauthorid | Wei, Z=53064846200 | en_HK |
dc.identifier.scopusauthorid | Wang, W=55195156700 | en_HK |
dc.identifier.citeulike | 9631504 | - |
dc.identifier.issnl | 2045-2322 | - |