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Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis

Overview of attention for article published in BMC Medical Genomics, June 2012
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1 tweeter

Citations

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51 Mendeley
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Title
Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis
Published in
BMC Medical Genomics, June 2012
DOI 10.1186/1755-8794-5-23
Pubmed ID
Authors

Peter Kupfer, Peter Kupfer, Reinhard Guthke, Dirk Pohlers, Rene Huber, Dirk Koczan, Raimund W Kinne

Abstract

Batch effects due to sample preparation or array variation (type, charge, and/or platform) may influence the results of microarray experiments and thus mask and/or confound true biological differences. Of the published approaches for batch correction, the algorithm "Combating Batch Effects When Combining Batches of Gene Expression Microarray Data" (ComBat) appears to be most suitable for small sample sizes and multiple batches.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
United Kingdom 1 2%
New Zealand 1 2%
Argentina 1 2%
Denmark 1 2%
Unknown 46 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Ph. D. Student 12 24%
Student > Master 6 12%
Student > Bachelor 4 8%
Professor > Associate Professor 2 4%
Other 5 10%
Unknown 7 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 24%
Biochemistry, Genetics and Molecular Biology 11 22%
Medicine and Dentistry 7 14%
Unspecified 3 6%
Computer Science 3 6%
Other 7 14%
Unknown 8 16%

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 09 June 2012.
All research outputs
#2,016,338
of 3,622,349 outputs
Outputs from BMC Medical Genomics
#141
of 236 outputs
Outputs of similar age
#33,496
of 73,326 outputs
Outputs of similar age from BMC Medical Genomics
#10
of 15 outputs
Altmetric has tracked 3,622,349 research outputs across all sources so far. This one is in the 25th percentile – i.e., 25% of other outputs scored the same or lower than it.
So far Altmetric has tracked 236 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 25th percentile – i.e., 25% 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 73,326 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.