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Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment

Overview of attention for article published in BMC Pulmonary Medicine, May 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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1 policy source
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36 Mendeley
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Title
Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment
Published in
BMC Pulmonary Medicine, May 2016
DOI 10.1186/s12890-016-0250-0
Pubmed ID
Authors

Andrei-Tudor Cernomaz, Ina Iuliana Macovei, Ionut Pavel, Carmen Grigoriu, Mihai Marinca, Florent Baty, Simona Peter, Radu Zonda, Martin Brutsche, Bogdan- Dragos Grigoriu

Abstract

The epidermal growth factor receptor (EGFR) mutation status assessment has become increasingly important given the significant impact of tyrosine kinase inhibitors in lung cancer management. Our aim was to compare real life operational characteristics for three EGFR mutation assays - two targeted approaches and a next generation sequencing (NGS) technique. EGFR mutation status was assessed for lung adenocarcinoma samples (formalin fixed- paraffin embedded samples) using qPCR, SNaPshot and NGS (Ion Torrent™) techniques. A total of 15 high clinical significance mutations were identified by at least one technique from the total of 64 samples. All mutations were identified by the TaqMan qPCR technique while SNaPshot in conjunction with fragment analysis identified 11 EGFR mutations. The NGS approach followed by an automatic analysis using the default calling parameters identified 10 mutations from the SNaPshot/qPCR panel and other three insertions, five point mutations and 58 silent variants; manual data review identified all 15 high significance mutations. Performance was similar for high tumor content samples but careful data analysis and post hoc variant calling filter alterations were necessary in order to obtain robust results from low tumor content samples by NGS. NGS is able to generate a comprehensive mutational profile albeit at a higher cost and workload. Result interpretation should take into account not only general run parameters such as mean read depth but also relative coverage and read distribution; currently there is an acute need to define firm recommendations/standards concerning NGS data interpretation and quality control.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 35 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 22%
Researcher 6 17%
Other 5 14%
Student > Bachelor 5 14%
Student > Master 3 8%
Other 4 11%
Unknown 5 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 31%
Medicine and Dentistry 8 22%
Nursing and Health Professions 2 6%
Computer Science 2 6%
Unspecified 1 3%
Other 4 11%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 08 November 2023.
All research outputs
#7,829,314
of 25,081,419 outputs
Outputs from BMC Pulmonary Medicine
#624
of 2,221 outputs
Outputs of similar age
#114,383
of 341,100 outputs
Outputs of similar age from BMC Pulmonary Medicine
#13
of 41 outputs
Altmetric has tracked 25,081,419 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 2,221 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 341,100 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.