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At least two well-spaced samples are needed to genotype a solid tumor

Overview of attention for article published in BMC Cancer, March 2016
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Mentioned by

2 tweeters


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23 Mendeley
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At least two well-spaced samples are needed to genotype a solid tumor
Published in
BMC Cancer, March 2016
DOI 10.1186/s12885-016-2202-8
Pubmed ID

Kimberly Siegmund, Darryl Shibata


Human cancers are often sequenced to identify mutations. However, cancers are spatially heterogeneous populations with public mutations in all cells and private mutations in some cells. Without empiric knowledge of how mutations are distributed within a solid tumor it is uncertain whether single or multiple samples adequately sample its heterogeneity. Using a cohort of 12 human colorectal tumors with well-validated mutations, the abilities to correctly classify public and private mutations were tested (paired t-test) with one sample or two samples obtained from opposite tumor sides. Two samples were significantly better than a single sample for correctly identifying public (99 % versus 97 %) and private mutations (85 % versus 46 %). Confounding single sample accuracy was that many private mutations appeared "clonal" in individual samples. Two samples detected the most frequent private mutations in 11 of the 12 tumors. Two spatially-separated samples efficiently distinguish public from private mutations because private mutations common in one specimen are usually less frequent or absent in another sample. The patch-like private mutation topography in most colorectal tumors inherently limits the information in single tumor samples. The correct identification of public and private mutations may aid efforts to target mutations present in all tumor cells.

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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 4%
Germany 1 4%
France 1 4%
Canada 1 4%
Unknown 19 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 17%
Researcher 4 17%
Professor > Associate Professor 3 13%
Professor 3 13%
Other 2 9%
Other 5 22%
Unknown 2 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 35%
Agricultural and Biological Sciences 7 30%
Medicine and Dentistry 2 9%
Linguistics 1 4%
Mathematics 1 4%
Other 2 9%
Unknown 2 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 01 April 2016.
All research outputs
of 16,534,657 outputs
Outputs from BMC Cancer
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Outputs of similar age
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Outputs of similar age from BMC Cancer
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Altmetric has tracked 16,534,657 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,070 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 51% 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 268,369 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them