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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.
|
|---|---|
| Chapter number | 20 |
| Book title |
Molecular Typing of Blood Cell Antigens
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-2690-9_20 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-2689-3, 978-1-4939-2690-9
|
| Authors |
Boegel, Sebastian, Scholtalbers, Jelle, Löwer, Martin, Sahin, Ugur, Castle, John C, Sebastian Boegel, Jelle Scholtalbers, Martin Löwer, Ugur Sahin, John C. Castle, Castle, John C. |
| Abstract |
Next-generation sequencing (NGS) enables high-throughput transcriptome profiling using the RNA-Seq assay, resulting in billions of short sequence reads. Worldwide adoption has been rapid: many laboratories worldwide generate transcriptome sequence reads daily. Here, we describe methods for obtaining a sample's human leukocyte antigen (HLA) class I and II types and HLA expression using standard NGS RNA-Seq sequence reads. We demonstrate the application using our algorithm, seq2HLA, and a publicly available RNA-Seq dataset from the Burkitt lymphoma cell line Raji. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 30% |
| Student > Doctoral Student | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Student > Ph. D. Student | 2 | 7% |
| Professor | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 9 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 26% |
| Biochemistry, Genetics and Molecular Biology | 4 | 15% |
| Agricultural and Biological Sciences | 3 | 11% |
| Immunology and Microbiology | 2 | 7% |
| Computer Science | 2 | 7% |
| Other | 0 | 0% |
| Unknown | 9 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 26 February 2021.
All research outputs
#3,657,832
of 25,177,382 outputs
Outputs from Methods in molecular biology
#831
of 14,132 outputs
Outputs of similar age
#49,900
of 365,313 outputs
Outputs of similar age from Methods in molecular biology
#52
of 996 outputs
Altmetric has tracked 25,177,382 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,132 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 93% 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 365,313 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 996 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 94% of its contemporaries.