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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
An overview of the analysis of next generation sequencing data.
|
|---|---|
| Chapter number | 16 |
| Book title |
Next Generation Microarray Bioinformatics
|
| Published in |
Methods in molecular biology, January 2012
|
| DOI | 10.1007/978-1-61779-400-1_16 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-399-8, 978-1-61779-400-1
|
| Authors |
Andreas Gogol-Döring, Wei Chen, Gogol-Döring, Andreas, Chen, Wei |
| Abstract |
Next generation sequencing is a common and versatile tool for biological and medical research. We describe the basic steps for analyzing next generation sequencing data, including quality checking and mapping to a reference genome. We also explain the further data analysis for three common applications of next generation sequencing: variant detection, RNA-seq, and ChIP-seq. |
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 % |
|---|---|---|
| United States | 2 | 33% |
| United Kingdom | 1 | 17% |
| Belgium | 1 | 17% |
| Canada | 1 | 17% |
| France | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| Italy | 2 | <1% |
| Belgium | 2 | <1% |
| United Kingdom | 2 | <1% |
| Norway | 1 | <1% |
| Denmark | 1 | <1% |
| Sweden | 1 | <1% |
| Unknown | 240 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 78 | 31% |
| Researcher | 43 | 17% |
| Student > Master | 38 | 15% |
| Student > Doctoral Student | 18 | 7% |
| Student > Bachelor | 17 | 7% |
| Other | 31 | 12% |
| Unknown | 27 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 88 | 35% |
| Biochemistry, Genetics and Molecular Biology | 64 | 25% |
| Medicine and Dentistry | 19 | 8% |
| Immunology and Microbiology | 8 | 3% |
| Computer Science | 7 | 3% |
| Other | 34 | 13% |
| Unknown | 32 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 03 July 2015.
All research outputs
#2,734,557
of 22,659,164 outputs
Outputs from Methods in molecular biology
#525
of 13,019 outputs
Outputs of similar age
#22,462
of 244,041 outputs
Outputs of similar age from Methods in molecular biology
#36
of 473 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,019 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 95% 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 244,041 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 90% of its contemporaries.
We're also able to compare this research output to 473 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 92% of its contemporaries.