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X Demographics
Mendeley readers
Attention Score in Context
| Title |
tcR: an R package for T cell receptor repertoire advanced data analysis
|
|---|---|
| Published in |
BMC Bioinformatics, May 2015
|
| DOI | 10.1186/s12859-015-0613-1 |
| Pubmed ID | |
| Authors |
Vadim I. Nazarov, Mikhail V. Pogorelyy, Ekaterina A. Komech, Ivan V. Zvyagin, Dmitry A. Bolotin, Mikhail Shugay, Dmitry M. Chudakov, Yury B. Lebedev, Ilgar Z. Mamedov |
| Abstract |
The Immunoglobulins (IG) and the T cell receptors (TR) play the key role in antigen recognition during the adaptive immune response. Recent progress in next-generation sequencing technologies has provided an opportunity for the deep T cell receptor repertoire profiling. However, a specialised software is required for the rational analysis of massive data generated by next-generation sequencing. Here we introduce tcR, a new R package, representing a platform for the advanced analysis of T cell receptor repertoires, which includes diversity measures, shared T cell receptor sequences identification, gene usage statistics computation and other widely used methods. The tool has proven its utility in recent research studies. tcR is an R package for the advanced analysis of T cell receptor repertoires after primary TR sequences extraction from raw sequencing reads. The stable version can be directly installed from The Comprehensive R Archive Network ( http://cran.r-project.org/mirrors.html ). The source code and development version are available at tcR GitHub ( http://imminfo.github.io/tcr/ ) along with the full documentation and typical usage examples. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 25% |
| United Kingdom | 1 | 8% |
| Unknown | 8 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Scientists | 5 | 42% |
Mendeley readers
The data shown below were compiled from readership statistics for 278 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | <1% |
| Netherlands | 1 | <1% |
| Austria | 1 | <1% |
| Australia | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 272 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 67 | 24% |
| Student > Ph. D. Student | 51 | 18% |
| Student > Master | 35 | 13% |
| Student > Bachelor | 21 | 8% |
| Student > Doctoral Student | 14 | 5% |
| Other | 45 | 16% |
| Unknown | 45 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 77 | 28% |
| Biochemistry, Genetics and Molecular Biology | 53 | 19% |
| Medicine and Dentistry | 35 | 13% |
| Immunology and Microbiology | 33 | 12% |
| Computer Science | 11 | 4% |
| Other | 19 | 7% |
| Unknown | 50 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 14 April 2023.
All research outputs
#1,433,145
of 24,071,812 outputs
Outputs from BMC Bioinformatics
#214
of 7,498 outputs
Outputs of similar age
#18,462
of 270,420 outputs
Outputs of similar age from BMC Bioinformatics
#4
of 127 outputs
Altmetric has tracked 24,071,812 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,498 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% 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 270,420 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 93% of its contemporaries.
We're also able to compare this research output to 127 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 97% of its contemporaries.