DaMold: A data‐mining platform for variant annotation and visualization in molecular diagnostics research. Issue 7 (30th May 2017)
- Record Type:
- Journal Article
- Title:
- DaMold: A data‐mining platform for variant annotation and visualization in molecular diagnostics research. Issue 7 (30th May 2017)
- Main Title:
- DaMold: A data‐mining platform for variant annotation and visualization in molecular diagnostics research
- Authors:
- Pandey, Ram Vinay
Pabinger, Stephan
Kriegner, Albert
Weinhäusel, Andreas - Abstract:
- Abstract : Single NGS based genetic test yields hundreds to thousands of variants, thus the current challenge is to meaningfully interpret the data and select potential pathogenic mutations for clinician and molecular biologists. To overcome such challenges, we have developed DaMold, a web‐based, and user‐friendly tool to filter, annotate, cross‐link, and visualize NGS, Sanger, and hotspot variants in intuitive manner. DaMold provides information from clinical resources (i.e. ClinVar, Cosmic databases) to identify the pathogenic mutations. Abstract: Next‐generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time‐consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross‐referencing, and visualization. This tool would allow variants to be processed in an automated and high‐throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing‐read processing and variantAbstract : Single NGS based genetic test yields hundreds to thousands of variants, thus the current challenge is to meaningfully interpret the data and select potential pathogenic mutations for clinician and molecular biologists. To overcome such challenges, we have developed DaMold, a web‐based, and user‐friendly tool to filter, annotate, cross‐link, and visualize NGS, Sanger, and hotspot variants in intuitive manner. DaMold provides information from clinical resources (i.e. ClinVar, Cosmic databases) to identify the pathogenic mutations. Abstract: Next‐generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time‐consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross‐referencing, and visualization. This tool would allow variants to be processed in an automated and high‐throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing‐read processing and variant identification, but an automated variant filtering, annotation, cross‐referencing, and visualization tool is still lacking. To fulfill these requirements, we developed DaMold, a Web‐based, user‐friendly tool that can filter and annotate variants and can access and compile information from 37 resources. It is easy to use, provides flexible input options, and accepts variants from NGS and Sanger sequencing as well as hotspots in VCF and BED formats. DaMold is available as an online application athttp://damold.platomics.com/index.html, and as a Docker container and virtual machine athttps://sourceforge.net/projects/damold/ . … (more)
- Is Part Of:
- Human mutation. Volume 38:Issue 7(2017)
- Journal:
- Human mutation
- Issue:
- Volume 38:Issue 7(2017)
- Issue Display:
- Volume 38, Issue 7 (2017)
- Year:
- 2017
- Volume:
- 38
- Issue:
- 7
- Issue Sort Value:
- 2017-0038-0007-0000
- Page Start:
- 778
- Page End:
- 787
- Publication Date:
- 2017-05-30
- Subjects:
- database cross‐reference -- diagnostic sequencing -- genetic testing -- hotspot mutation -- mutation testing -- next‐generation sequencing -- Sanger sequencing -- variant annotation -- variant effect prediction
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.23227 ↗
- 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
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British Library HMNTS - ELD Digital store - Ingest File:
- 8109.xml