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Reconstructing cancer karyotypes from short read data: the half empty and half full glass

Overview of attention for article published in BMC Bioinformatics, November 2017
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Title
Reconstructing cancer karyotypes from short read data: the half empty and half full glass
Published in
BMC Bioinformatics, November 2017
DOI 10.1186/s12859-017-1929-9
Pubmed ID
Authors

Rami Eitan, Ron Shamir

Abstract

During cancer progression genomes undergo point mutations as well as larger segmental changes. The latter include, among others, segmental deletions duplications, translocations and inversions.The result is a highly complex, patient-specific cancer karyotype. Using high-throughput technologies of deep sequencing and microarrays it is possible to interrogate a cancer genome and produce chromosomal copy number profiles and a list of breakpoints ("jumps") relative to the normal genome. This information is very detailed but local, and does not give the overall picture of the cancer genome. One of the basic challenges in cancer genome research is to use such information to infer the cancer karyotype. We present here an algorithmic approach, based on graph theory and integer linear programming, that receives segmental copy number and breakpoint data as input and produces a cancer karyotype that is most concordant with them. We used simulations to evaluate the utility of our approach, and applied it to real data. By using a simulation model, we were able to estimate the correctness and robustness of the algorithm in a spectrum of scenarios. Under our base scenario, designed according to observations in real data, the algorithm correctly inferred 69% of the karyotypes. However, when using less stringent correctness metrics that account for incomplete and noisy data, 87% of the reconstructed karyotypes were correct. Furthermore, in scenarios where the data were very clean and complete, accuracy rose to 90%-100%. Some examples of analysis of real data, and the reconstructed karyotypes suggested by our algorithm, are also presented. While reconstruction of complete, perfect karyotype based on short read data is very hard, a large fraction of the reconstruction will still be correct and can provide useful information.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 24%
Researcher 4 16%
Student > Ph. D. Student 4 16%
Professor > Associate Professor 3 12%
Professor 2 8%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Computer Science 7 28%
Agricultural and Biological Sciences 6 24%
Biochemistry, Genetics and Molecular Biology 5 20%
Medicine and Dentistry 2 8%
Mathematics 1 4%
Other 2 8%
Unknown 2 8%
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 02 March 2018.
All research outputs
#15,483,707
of 23,008,860 outputs
Outputs from BMC Bioinformatics
#5,398
of 7,315 outputs
Outputs of similar age
#203,337
of 324,977 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 159 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,315 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 324,977 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.