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Attention Score in Context
| Title |
Assessing telomeric DNA content in pediatric cancers using whole-genome sequencing data
|
|---|---|
| Published in |
Genome Biology, December 2012
|
| DOI | 10.1186/gb-2012-13-12-r113 |
| Pubmed ID | |
| Authors |
Matthew Parker, Xiang Chen, Armita Bahrami, James Dalton, Michael Rusch, Gang Wu, John Easton, Nai-Kong Cheung, Michael Dyer, Elaine R Mardis, Richard K Wilson, Charles Mullighan, Richard Gilbertson, Suzanne J Baker, Gerard Zambetti, David W Ellison, James R Downing, Jinghui Zhang, Pediatric Cancer Genome Project |
| Abstract |
ABSTRACT: BACKGROUND: Telomeres are the protective arrays of tandem TTAGGG sequence and associated proteins at the termini of chromosomes. Telomeres shorten at each cell division due to the end-replication problem and are maintained above a critical threshold in malignant cancer cells to prevent cellular senescence or apoptosis. With the recent advances in massive parallel sequencing, assessing telomere content in the context of other cancer genomic aberrations becomes an attractive possibility. We present the first comprehensive analysis of telomeric DNA content change in tumors using whole-genome sequencing data from 235 pediatric cancers. RESULTS: To measure telomeric DNA content, we counted telomeric reads containing TTAGGGx4 or CCCTAAx4 and normalized to the average genomic coverage. Changes in telomeric DNA content in tumor genomes were clustered using a Bayesian Information Criterion to determine loss, no change, or gain. Using this approach, we found that the pattern of telomeric DNA alteration varies dramatically across the landscape of pediatric malignancies: telomere gain was found in 32% of solid tumors, 4% of brain tumors and 0% of hematopoietic malignancies. The results were validated by three independent experimental approaches and reveal significant association of telomere gain with the frequency of somatic sequence mutations and structural variations. CONCLUSIONS: Telomere DNA content measurement using whole-genome sequencing data is a reliable approach that can generate useful insights into the landscape of the cancer genome. Measuring the change in telomeric DNA during malignant progression is likely to be a useful metric when considering telomeres in the context of the whole genome. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 43% |
| India | 1 | 14% |
| France | 1 | 14% |
| Denmark | 1 | 14% |
| United Kingdom | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 43% |
| Members of the public | 3 | 43% |
| Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 3% |
| France | 1 | <1% |
| Canada | 1 | <1% |
| Russia | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 100 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 33 | 31% |
| Student > Ph. D. Student | 28 | 26% |
| Other | 7 | 7% |
| Professor > Associate Professor | 6 | 6% |
| Student > Bachelor | 5 | 5% |
| Other | 12 | 11% |
| Unknown | 16 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 45 | 42% |
| Biochemistry, Genetics and Molecular Biology | 21 | 20% |
| Medicine and Dentistry | 8 | 7% |
| Computer Science | 5 | 5% |
| Engineering | 2 | 2% |
| Other | 8 | 7% |
| Unknown | 18 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 47. 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 04 February 2014.
All research outputs
#884,500
of 25,373,627 outputs
Outputs from Genome Biology
#597
of 4,467 outputs
Outputs of similar age
#6,601
of 286,218 outputs
Outputs of similar age from Genome Biology
#4
of 42 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 86% 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 286,218 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.