The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility.
This research output has an Altmetric Attention Score of 4. 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 January 2016.
All research outputs
#11,164,534
of 34,357,314 outputs
Outputs from PLOS ONE
#95,535
of 224,504 outputs
Outputs of similar age
#75,722
of 221,580 outputs
Outputs of similar age from PLOS ONE
#2,381
of 5,266 outputs
Altmetric has tracked 34,357,314 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 224,504 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has gotten more attention than average, scoring higher than 57% 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 221,580 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 5,266 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
