| Title |
Universal Count Correction for High-Throughput Sequencing
|
|---|---|
| Published in |
PLoS Computational Biology, March 2014
|
| DOI | 10.1371/journal.pcbi.1003494 |
| Pubmed ID | |
| Authors |
Tatsunori B. Hashimoto, Matthew D. Edwards, David K. Gifford |
| Abstract |
We show that existing RNA-seq, DNase-seq, and ChIP-seq data exhibit overdispersed per-base read count distributions that are not matched to existing computational method assumptions. To compensate for this overdispersion we introduce a nonparametric and universal method for processing per-base sequencing read count data called FIXSEQ. We demonstrate that FIXSEQ substantially improves the performance of existing RNA-seq, DNase-seq, and ChIP-seq analysis tools when compared with existing alternatives. |
X Demographics
The data shown below were collected from the profiles of 47 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 | 17 | 36% |
| France | 5 | 11% |
| Germany | 3 | 6% |
| United Kingdom | 2 | 4% |
| Sweden | 1 | 2% |
| Mexico | 1 | 2% |
| South Africa | 1 | 2% |
| India | 1 | 2% |
| Canada | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 15 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 28 | 60% |
| Members of the public | 18 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 7% |
| Germany | 3 | 2% |
| Canada | 3 | 2% |
| Spain | 2 | 1% |
| Denmark | 2 | 1% |
| Norway | 2 | 1% |
| Austria | 1 | <1% |
| Sweden | 1 | <1% |
| Finland | 1 | <1% |
| Other | 9 | 5% |
| Unknown | 157 | 81% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 62 | 32% |
| Student > Ph. D. Student | 59 | 30% |
| Professor > Associate Professor | 11 | 6% |
| Student > Master | 11 | 6% |
| Professor | 10 | 5% |
| Other | 28 | 14% |
| Unknown | 13 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 100 | 52% |
| Biochemistry, Genetics and Molecular Biology | 46 | 24% |
| Computer Science | 12 | 6% |
| Mathematics | 5 | 3% |
| Environmental Science | 3 | 2% |
| Other | 12 | 6% |
| Unknown | 16 | 8% |