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Interpreting whole genome and exome sequencing data of individual gastric cancer samples

Overview of attention for article published in BMC Genomics, July 2017
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2 tweeters

Citations

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40 Mendeley
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Title
Interpreting whole genome and exome sequencing data of individual gastric cancer samples
Published in
BMC Genomics, July 2017
DOI 10.1186/s12864-017-3895-z
Pubmed ID
Authors

Daniela Esser, Niklas Holze, Jochen Haag, Stefan Schreiber, Sandra Krüger, Viktoria Warneke, Philip Rosenstiel, Christoph Röcken

Abstract

Gastric cancer is the fourth most common cancer and the second leading cause of cancer death worldwide. In order to understand the genetic background, we sequenced the whole exome and the whole genome of one microsatellite stable as well as one microsatellite unstable tumor and the matched healthy tissue on two different NGS platforms. We here aimed to provide a comparative approach for individual clinical tumor sequencing and annotation using different sequencing technologies and mutation calling algorithms. We applied a population-based whole genome resource as a novel pathway-based filter for interpretation of genomic alterations from single nucleotide variations (SNV), indels, and large structural variations. In addition to a comparison with tumor genome database resources and a filtering approach using data from the 1000 Genomes Project, we performed pyrosequencing analysis and immunohistochemistry in a large cohort of 428 independent gastric cancer cases. We here provide an example comparing the usefulness and potential pitfalls of different technologies for a clinical interpretation of genomic sequence data of individual gastric cancer samples. Using different filtering approaches, we identified a multitude of novel potentially damaging mutations and could show a validated association between a mutation in GNAS and gastric cancer.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 10 25%
Researcher 6 15%
Student > Ph. D. Student 5 13%
Student > Master 4 10%
Other 3 8%
Other 7 18%
Unknown 5 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 30%
Agricultural and Biological Sciences 7 18%
Medicine and Dentistry 7 18%
Engineering 2 5%
Immunology and Microbiology 2 5%
Other 3 8%
Unknown 7 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 March 2018.
All research outputs
#13,970,765
of 18,187,474 outputs
Outputs from BMC Genomics
#6,665
of 9,540 outputs
Outputs of similar age
#189,429
of 274,977 outputs
Outputs of similar age from BMC Genomics
#4
of 4 outputs
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So far Altmetric has tracked 9,540 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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