| Title |
Single-cell RNAseq for the study of isoforms—how is that possible?
|
|---|---|
| Published in |
Genome Biology, August 2018
|
| DOI | 10.1186/s13059-018-1496-z |
| Pubmed ID | |
| Authors |
Ángeles Arzalluz-Luque, Ana Conesa |
| Abstract |
Single-cell RNAseq and alternative splicing studies have recently become two of the most prominent applications of RNAseq. However, the combination of both is still challenging, and few research efforts have been dedicated to the intersection between them. Cell-level insight on isoform expression is required to fully understand the biology of alternative splicing, but it is still an open question to what extent isoform expression analysis at the single-cell level is actually feasible. Here, we establish a set of four conditions that are required for a successful single-cell-level isoform study and evaluate how these conditions are met by these technologies in published research. |
X Demographics
The data shown below were collected from the profiles of 81 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 | 20 | 25% |
| Spain | 8 | 10% |
| Australia | 8 | 10% |
| France | 7 | 9% |
| United Kingdom | 7 | 9% |
| Germany | 3 | 4% |
| Venezuela, Bolivarian Republic of | 2 | 2% |
| South Africa | 1 | 1% |
| Norway | 1 | 1% |
| Other | 4 | 5% |
| Unknown | 20 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 50 | 62% |
| Members of the public | 28 | 35% |
| Practitioners (doctors, other healthcare professionals) | 1 | 1% |
| Science communicators (journalists, bloggers, editors) | 1 | 1% |
| Unknown | 1 | 1% |
Mendeley readers
The data shown below were compiled from readership statistics for 306 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 306 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 74 | 24% |
| Researcher | 47 | 15% |
| Student > Master | 29 | 9% |
| Student > Bachelor | 27 | 9% |
| Student > Doctoral Student | 13 | 4% |
| Other | 48 | 16% |
| Unknown | 68 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 98 | 32% |
| Agricultural and Biological Sciences | 62 | 20% |
| Computer Science | 20 | 7% |
| Medicine and Dentistry | 15 | 5% |
| Neuroscience | 10 | 3% |
| Other | 26 | 8% |
| Unknown | 75 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 54. 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 08 February 2024.
All research outputs
#804,294
of 25,728,350 outputs
Outputs from Genome Biology
#527
of 4,508 outputs
Outputs of similar age
#16,836
of 342,287 outputs
Outputs of similar age from Genome Biology
#11
of 61 outputs
Altmetric has tracked 25,728,350 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,508 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.5. This one has done well, scoring higher than 88% of its peers.
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We're also able to compare this research output to 61 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.