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An integrative approach for efficient analysis of whole genome bisulfite sequencing data

Overview of attention for article published in BMC Genomics, December 2015
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Title
An integrative approach for efficient analysis of whole genome bisulfite sequencing data
Published in
BMC Genomics, December 2015
DOI 10.1186/1471-2164-16-s12-s14
Pubmed ID
Authors

Jong-Hun Lee, Sung-Joon Park, Nakai Kenta

Abstract

Whole genome bisulfite sequencing (WGBS) is a high-throughput technique for profiling genome-wide DNA methylation at single nucleotide resolution. However, the applications of WGBS are limited by low accuracy resulting from bisulfite-induced damage on DNA fragments. Although many computer programs have been developed for accurate detecting, most of the programs have barely succeeded in improving either quantity or quality of the methylation results. To improve both, we attempted to develop a novel integration of most widely used bisulfite-read mappers: Bismark, BSMAP, and BS-seeker2. A comprehensive analysis of the three mappers revealed that the mapping results of the mappers were mutually complementary under diverse read conditions. Therefore, we sought to integrate the characteristics of the mappers by scoring them to gain robustness against artifacts. As a result, the integration significantly increased detection accuracy compared with the individual mappers. In addition, the amount of detected cytosine was higher than that by Bismark. Furthermore, the integration successfully reduced the fluctuation of detection accuracy induced by read conditions. We applied the integration to real WGBS samples and succeeded in classifying the samples according to the originated tissues by both CpG and CpH methylation patterns. In this study, we improved both quality and quantity of methylation results from WGBS data by integrating the mapping results of three bisulfite-read mappers. Also, we succeeded in combining and comparing WGBS samples by reducing the effects of read heterogeneity on methylation detection. This study contributes to DNA methylation researches by improving efficiency of methylation detection from WGBS data and facilitating the comprehensive analysis of public WGBS data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 47 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 10 21%
Student > Bachelor 4 8%
Student > Master 4 8%
Student > Doctoral Student 2 4%
Other 5 10%
Unknown 13 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 33%
Biochemistry, Genetics and Molecular Biology 14 29%
Engineering 2 4%
Computer Science 2 4%
Nursing and Health Professions 1 2%
Other 0 0%
Unknown 13 27%
Attention Score in Context

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 19 December 2015.
All research outputs
#18,432,465
of 22,835,198 outputs
Outputs from BMC Genomics
#8,183
of 10,655 outputs
Outputs of similar age
#280,827
of 389,036 outputs
Outputs of similar age from BMC Genomics
#306
of 342 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 342 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.