↓ Skip to main content

TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets

Overview of attention for article published in BMC Bioinformatics, June 2010
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

twitter
1 tweeter
patent
1 patent

Citations

dimensions_citation
180 Dimensions

Readers on

mendeley
256 Mendeley
citeulike
5 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets
Published in
BMC Bioinformatics, June 2010
DOI 10.1186/1471-2105-11-341
Pubmed ID
Authors

Robert Schmieder, Yan Wei Lim, Forest Rohwer, Robert Edwards

Abstract

Sequencing metagenomes that were pre-amplified with primer-based methods requires the removal of the additional tag sequences from the datasets. The sequenced reads can contain deletions or insertions due to sequencing limitations, and the primer sequence may contain ambiguous bases. Furthermore, the tag sequence may be unavailable or incorrectly reported. Because of the potential for downstream inaccuracies introduced by unwanted sequence contaminations, it is important to use reliable tools for pre-processing sequence data.

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 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 8 3%
France 3 1%
United States 3 1%
United Kingdom 2 <1%
Chile 1 <1%
Norway 1 <1%
Colombia 1 <1%
India 1 <1%
Sweden 1 <1%
Other 5 2%
Unknown 230 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 72 28%
Student > Ph. D. Student 48 19%
Student > Master 40 16%
Student > Doctoral Student 18 7%
Student > Bachelor 17 7%
Other 40 16%
Unknown 21 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 149 58%
Biochemistry, Genetics and Molecular Biology 37 14%
Computer Science 10 4%
Environmental Science 9 4%
Medicine and Dentistry 8 3%
Other 14 5%
Unknown 29 11%

Attention Score in Context

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 10 December 2020.
All research outputs
#5,946,320
of 19,659,155 outputs
Outputs from BMC Bioinformatics
#2,428
of 6,636 outputs
Outputs of similar age
#34,171
of 107,513 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 19,659,155 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 6,636 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 61% 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 107,513 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 66% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them