| Title |
Copy number analysis by low coverage whole genome sequencing using ultra low-input DNA from formalin-fixed paraffin embedded tumor tissue
|
|---|---|
| Published in |
Genome Medicine, November 2016
|
| DOI | 10.1186/s13073-016-0375-z |
| Pubmed ID | |
| Authors |
Tanjina Kader, David L. Goode, Stephen Q. Wong, Jacquie Connaughton, Simone M. Rowley, Lisa Devereux, David Byrne, Stephen B. Fox, Gisela Mir Arnau, Richard W. Tothill, Ian G. Campbell, Kylie L. Gorringe |
| Abstract |
Unlocking clinically translatable genomic information, including copy number alterations (CNA), from formalin-fixed paraffin-embedded (FFPE) tissue is challenging due to low yields and degraded DNA. We describe a robust, cost-effective low-coverage whole genome sequencing (LC WGS) method for CNA detection using 5 ng of FFPE-derived DNA. CN profiles using 100 ng or 5 ng input DNA were highly concordant and comparable with molecular inversion probe (MIP) array profiles. LC WGS improved CN profiles of samples that performed poorly using MIP arrays. Our technique enables identification of driver and prognostic CNAs in archival patient samples previously deemed unsuitable for genomic analysis due to DNA limitations. |
X Demographics
The data shown below were collected from the profiles of 9 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 Kingdom | 4 | 44% |
| Montenegro | 1 | 11% |
| Sweden | 1 | 11% |
| India | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 78% |
| Members of the public | 1 | 11% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| China | 1 | <1% |
| Unknown | 110 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 27 | 24% |
| Student > Ph. D. Student | 18 | 16% |
| Student > Master | 15 | 13% |
| Student > Bachelor | 8 | 7% |
| Student > Doctoral Student | 7 | 6% |
| Other | 14 | 12% |
| Unknown | 24 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 26 | 23% |
| Agricultural and Biological Sciences | 20 | 18% |
| Medicine and Dentistry | 19 | 17% |
| Engineering | 4 | 4% |
| Computer Science | 3 | 3% |
| Other | 11 | 10% |
| Unknown | 30 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 24 March 2017.
All research outputs
#6,143,405
of 23,318,744 outputs
Outputs from Genome Medicine
#1,029
of 1,457 outputs
Outputs of similar age
#90,079
of 307,857 outputs
Outputs of similar age from Genome Medicine
#30
of 36 outputs
Altmetric has tracked 23,318,744 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 1,457 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.