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SeqPurge: highly-sensitive adapter trimming for paired-end NGS data

Overview of attention for article published in BMC Bioinformatics, May 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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6 X users

Citations

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184 Mendeley
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2 CiteULike
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Title
SeqPurge: highly-sensitive adapter trimming for paired-end NGS data
Published in
BMC Bioinformatics, May 2016
DOI 10.1186/s12859-016-1069-7
Pubmed ID
Authors

Marc Sturm, Christopher Schroeder, Peter Bauer

Abstract

Trimming of adapter sequences from short read data is a common preprocessing step during NGS data analysis. When performing paired-end sequencing, the overlap between forward and reverse read can be used to identify excess adapter sequences. This is exploited by several previously published adapter trimming tools. However, our evaluation on amplicon-based data shows that most of the current tools are not able to remove all adapter sequences and that adapter contamination may even lead to spurious variant calls. Here we present SeqPurge ( https://github.com/imgag/ngs-bits ), a highly-sensitive adapter trimmer that uses a probabilistic approach to detect the overlap between forward and reverse reads of Illumina sequencing data. SeqPurge can detect very short adapter sequences, even if only one base long. Compared to other adapter trimmers specifically designed for paired-end data, we found that SeqPurge achieves a higher sensitivity. The number of remaining adapter bases after trimming is reduced by up to 90 %, depending on the compared tool. In simulations with different error rates, we found that SeqPurge is also the most error-tolerant adapter trimmer in the comparison. SeqPurge achieves a very high sensitivity and a high error-tolerance, combined with a specificity and runtime that are comparable to other state-of-the-art adapter trimmers. The very good adapter trimming performance, complemented with additional features such as quality-based trimming and basic quality control, makes SeqPurge an excellent choice for the pre-processing of paired-end NGS data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
Germany 1 <1%
France 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 179 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 21%
Student > Ph. D. Student 35 19%
Student > Master 34 18%
Student > Bachelor 14 8%
Other 7 4%
Other 21 11%
Unknown 34 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 31%
Biochemistry, Genetics and Molecular Biology 52 28%
Computer Science 10 5%
Medicine and Dentistry 10 5%
Immunology and Microbiology 5 3%
Other 8 4%
Unknown 42 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 December 2017.
All research outputs
#13,174,456
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#3,692
of 7,418 outputs
Outputs of similar age
#140,994
of 306,775 outputs
Outputs of similar age from BMC Bioinformatics
#44
of 103 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 48th percentile – i.e., 48% 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 306,775 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 53% of its contemporaries.
We're also able to compare this research output to 103 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 57% of its contemporaries.