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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Single-Cell mRNA-Seq Using the Fluidigm C1 System and Integrated Fluidics Circuits
|
|---|---|
| Chapter number | 10 |
| Book title |
Gene Expression Analysis
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7834-2_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7833-5, 978-1-4939-7834-2
|
| Authors |
Haibiao Gong, Devin Do, Ramesh Ramakrishnan, Gong, Haibiao, Do, Devin, Ramakrishnan, Ramesh |
| Abstract |
Single-cell mRNA-seq is a valuable tool to dissect expression profiles and to understand the regulatory network of genes. Microfluidics is well suited for single-cell analysis owing both to the small volume of the reaction chambers and easiness of automation. Here we describe the workflow of single-cell mRNA-seq using C1 IFC, which can isolate and process up to 96 cells. Both on-chip procedure (lysis, reverse transcription, and preamplification PCR) and off-chip sequencing library preparation protocols are described. The workflow generates full-length mRNA information, which is more valuable compared to 3' end counting method for many applications. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 17% |
| Student > Doctoral Student | 3 | 9% |
| Student > Master | 3 | 9% |
| Researcher | 3 | 9% |
| Student > Bachelor | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 14 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 11 | 31% |
| Agricultural and Biological Sciences | 4 | 11% |
| Environmental Science | 1 | 3% |
| Computer Science | 1 | 3% |
| Immunology and Microbiology | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 14 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 17 May 2018.
All research outputs
#18,612,796
of 23,056,273 outputs
Outputs from Methods in molecular biology
#7,980
of 13,196 outputs
Outputs of similar age
#330,687
of 442,476 outputs
Outputs of similar age from Methods in molecular biology
#950
of 1,499 outputs
Altmetric has tracked 23,056,273 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,196 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 442,476 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.