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High-Throughput SuperSAGE for Digital Gene Expression Analysis of Multiple Samples Using Next Generation Sequencing

Overview of attention for article published in PLOS ONE, August 2010
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Title
High-Throughput SuperSAGE for Digital Gene Expression Analysis of Multiple Samples Using Next Generation Sequencing
Published in
PLOS ONE, August 2010
DOI 10.1371/journal.pone.0012010
Pubmed ID
Authors

Hideo Matsumura, Kentaro Yoshida, Shujun Luo, Eiji Kimura, Takahiro Fujibe, Zayed Albertyn, Roberto A. Barrero, Detlev H. Krüger, Günter Kahl, Gary P. Schroth, Ryohei Terauchi

Abstract

We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined "High-Throughput (HT-) SuperSAGE". SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes allow researchers to analyze digital tags from transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications are foreseen and several examples are provided in the present study, including analyses of laser-microdissected cells, biological replicates and tag extraction using different anchoring enzymes.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Chile 4 2%
Germany 3 2%
Italy 2 1%
Brazil 2 1%
Netherlands 1 <1%
Colombia 1 <1%
Austria 1 <1%
Cuba 1 <1%
Other 5 3%
Unknown 159 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 25%
Student > Ph. D. Student 44 24%
Student > Master 24 13%
Professor > Associate Professor 12 6%
Other 11 6%
Other 32 17%
Unknown 16 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 123 66%
Biochemistry, Genetics and Molecular Biology 23 12%
Medicine and Dentistry 5 3%
Environmental Science 4 2%
Computer Science 2 1%
Other 9 5%
Unknown 19 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 18 April 2012.
All research outputs
#14,724,504
of 22,662,201 outputs
Outputs from PLOS ONE
#122,860
of 193,504 outputs
Outputs of similar age
#75,488
of 94,303 outputs
Outputs of similar age from PLOS ONE
#607
of 751 outputs
Altmetric has tracked 22,662,201 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,504 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 33rd percentile – i.e., 33% 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 94,303 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 751 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.