Semi‐automated cancer genome analysis using high‐performance computing. Issue 10 (17th July 2017)
- Record Type:
- Journal Article
- Title:
- Semi‐automated cancer genome analysis using high‐performance computing. Issue 10 (17th July 2017)
- Main Title:
- Semi‐automated cancer genome analysis using high‐performance computing
- Authors:
- Crispatzu, Giuliano
Kulkarni, Pranav
Toliat, Mohammad R.
Nürnberg, Peter
Herling, Marco
Herling, Carmen D.
Frommolt, Peter - Abstract:
- Abstract : QuickNGS Cancer enables rapid and accurate analysis of cancer genomics data using a high‐performance compute cluster with minimum hands‐on time. A novel combination of a consensus calling approach with a multi‐step filtering strategy identifies mutations of key cancer genes in TCGA data which were missed by an already well‐established pipeline. Finally, QuickNGS Cancer discovered novel mutations in hematologic malignancies which could be confirmed by independent experiments. Abstract: Next‐generation sequencing (NGS) has turned from a new and experimental technology into a standard procedure for cancer genome studies and clinical investigation. While a multitude of software packages for cancer genome data analysis have been made available, these need to be combined into efficient analytical workflows that cover multiple aspects relevant to a clinical environment and that deliver handy results within a reasonable time frame. Here, we introduce QuickNGS Cancer as a new suite of bioinformatics pipelines that is focused on cancer genomics and significantly reduces the analytical hurdles that still limit a broader applicability of NGS technology, particularly to clinically driven research. QuickNGS Cancer allows a highly efficient analysis of a broad variety of NGS data types, specifically considering cancer‐specific issues, such as biases introduced by tumor impurity and aneuploidy or the assessment of genomic variations regarding their biomedical relevance. ItAbstract : QuickNGS Cancer enables rapid and accurate analysis of cancer genomics data using a high‐performance compute cluster with minimum hands‐on time. A novel combination of a consensus calling approach with a multi‐step filtering strategy identifies mutations of key cancer genes in TCGA data which were missed by an already well‐established pipeline. Finally, QuickNGS Cancer discovered novel mutations in hematologic malignancies which could be confirmed by independent experiments. Abstract: Next‐generation sequencing (NGS) has turned from a new and experimental technology into a standard procedure for cancer genome studies and clinical investigation. While a multitude of software packages for cancer genome data analysis have been made available, these need to be combined into efficient analytical workflows that cover multiple aspects relevant to a clinical environment and that deliver handy results within a reasonable time frame. Here, we introduce QuickNGS Cancer as a new suite of bioinformatics pipelines that is focused on cancer genomics and significantly reduces the analytical hurdles that still limit a broader applicability of NGS technology, particularly to clinically driven research. QuickNGS Cancer allows a highly efficient analysis of a broad variety of NGS data types, specifically considering cancer‐specific issues, such as biases introduced by tumor impurity and aneuploidy or the assessment of genomic variations regarding their biomedical relevance. It delivers highly reproducible analysis results ready for interpretation within only a few days after sequencing, as shown by a reanalysis of 140 tumor/normal pairs from The Cancer Genome Atlas (TCGA) in which QuickNGS Cancer detected a significant number of mutations in key cancer genes missed by a well‐established mutation calling pipeline. Finally, QuickNGS Cancer obtained several unexpected mutations in leukemias that could be confirmed by Sanger sequencing. … (more)
- Is Part Of:
- Human mutation. Volume 38:Issue 10(2017)
- Journal:
- Human mutation
- Issue:
- Volume 38:Issue 10(2017)
- Issue Display:
- Volume 38, Issue 10 (2017)
- Year:
- 2017
- Volume:
- 38
- Issue:
- 10
- Issue Sort Value:
- 2017-0038-0010-0000
- Page Start:
- 1325
- Page End:
- 1335
- Publication Date:
- 2017-07-17
- Subjects:
- analysis pipeline -- cancer genomics -- medical bioinformatics -- next‐generation sequencing
Human chromosome abnormalities -- Periodicals
Mutation (Biology) -- Periodicals
616.04205 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-1004 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/humu.23275 ↗
- Languages:
- English
- ISSNs:
- 1059-7794
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4336.217000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 4684.xml