| Title |
Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts
|
|---|---|
| Published in |
Genome Biology, October 2009
|
| DOI | 10.1186/gb-2009-10-10-r115 |
| Pubmed ID | |
| Authors |
Joshua Z Levin, Michael F Berger, Xian Adiconis, Peter Rogov, Alexandre Melnikov, Timothy Fennell, Chad Nusbaum, Levi A Garraway, Andreas Gnirke |
| Abstract |
Targeted RNA-Seq combines next-generation sequencing with capture of sequences from a relevant subset of a transcriptome. When testing by capturing sequences from a tumor cDNA library by hybridization to oligonucleotide probes specific for 467 cancer-related genes, this method showed high selectivity, improved mutation detection enabling discovery of novel chimeric transcripts, and provided RNA expression data. Thus, targeted RNA-Seq produces an enhanced view of the molecular state of a set of "high interest" genes. |
Mendeley readers
The data shown below were compiled from readership statistics for 369 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 15 | 4% |
| Germany | 4 | 1% |
| United Kingdom | 4 | 1% |
| Switzerland | 2 | <1% |
| Sweden | 2 | <1% |
| Australia | 2 | <1% |
| Norway | 2 | <1% |
| France | 1 | <1% |
| Italy | 1 | <1% |
| Other | 10 | 3% |
| Unknown | 326 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 119 | 32% |
| Student > Ph. D. Student | 79 | 21% |
| Professor > Associate Professor | 35 | 9% |
| Student > Master | 33 | 9% |
| Professor | 21 | 6% |
| Other | 55 | 15% |
| Unknown | 27 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 211 | 57% |
| Biochemistry, Genetics and Molecular Biology | 55 | 15% |
| Medicine and Dentistry | 43 | 12% |
| Computer Science | 11 | 3% |
| Engineering | 5 | 1% |
| Other | 15 | 4% |
| Unknown | 29 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 06 December 2023.
All research outputs
#2,863,996
of 25,374,917 outputs
Outputs from Genome Biology
#2,197
of 4,467 outputs
Outputs of similar age
#9,694
of 106,169 outputs
Outputs of similar age from Genome Biology
#7
of 37 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% 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 gotten more attention than average, scoring higher than 50% 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 106,169 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 90% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.