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Use of the QIAGEN GeneReader NGS system for detection of KRAS mutations, validated by the QIAGEN Therascreen PCR kit and alternative NGS platform

Overview of attention for article published in BMC Cancer, May 2017
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Title
Use of the QIAGEN GeneReader NGS system for detection of KRAS mutations, validated by the QIAGEN Therascreen PCR kit and alternative NGS platform
Published in
BMC Cancer, May 2017
DOI 10.1186/s12885-017-3328-z
Pubmed ID
Authors

Agus Darwanto, Anne-Mette Hein, Sascha Strauss, Yi Kong, Andrew Sheridan, Dan Richards, Eric Lader, Monika Ngowe, Timothy Pelletier, Danielle Adams, Austin Ricker, Nishit Patel, Andreas Kühne, Simon Hughes, Dan Shiffman, Dirk Zimmermann, Kai te Kaat, Thomas Rothmann

Abstract

The detection of somatic mutations in primary tumors is critical for the understanding of cancer evolution and targeting therapy. Multiple technologies have been developed to enable the detection of such mutations. Next generation sequencing (NGS) is a new platform that is gradually becoming the technology of choice for genotyping cancer samples, owing to its ability to simultaneously interrogate many genomic loci at massively high efficiency and increasingly lower cost. However, multiple barriers still exist for its broader adoption in clinical research practice, such as fragmented workflow and complex bioinformatics analysis and interpretation. We performed validation of the QIAGEN GeneReader NGS System using the QIAact Actionable Insights Tumor Panel, focusing on clinically meaningful mutations by using DNA extracted from formalin-fixed paraffin-embedded (FFPE) colorectal tissue with known KRAS mutations. The performance of the GeneReader was evaluated and compared to data generated from alternative technologies (PCR and pyrosequencing) as well as an alternative NGS platform. The results were further confirmed with Sanger sequencing. The data generated from the GeneReader achieved 100% concordance with reference technologies. Furthermore, the GeneReader workflow provides a truly integrated workflow, eliminating artifacts resulting from routine sample preparation; and providing up-to-date interpretation of test results. The GeneReader NGS system offers an effective and efficient method to identify somatic (KRAS) cancer mutations.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Student > Bachelor 9 19%
Student > Master 5 11%
Other 4 9%
Student > Ph. D. Student 3 6%
Other 7 15%
Unknown 8 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 30%
Agricultural and Biological Sciences 7 15%
Medicine and Dentistry 6 13%
Computer Science 3 6%
Nursing and Health Professions 2 4%
Other 4 9%
Unknown 11 23%
Attention Score in Context

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 13 March 2018.
All research outputs
#18,590,133
of 23,026,672 outputs
Outputs from BMC Cancer
#5,463
of 8,362 outputs
Outputs of similar age
#239,134
of 313,778 outputs
Outputs of similar age from BMC Cancer
#88
of 142 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,362 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,778 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.