Evidence map›Paper›PMID 26922377›Full record

ArticleBMC genomics2016

Targeted alignment and end repair elimination increase alignment and methylation measure accuracy for reduced representation bisulfite sequencing data.

Saurabh Baheti, Rahul Kanwar, Meike Goelzenleuchter, Jean-Pierre A Kocher, Andreas S Beutler, Zhifu Sun

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 100% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Saurabh BahetiDivision of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. baheti.saurabh@mayo.edu.
Rahul KanwarDepartment of Medical Oncology, Mayo Clinic, Rochester, MN, 55905, USA. kanwar.rahul@mayo.edu.
Meike GoelzenleuchterDepartment of Medical Oncology, Mayo Clinic, Rochester, MN, 55905, USA. meike.goe@gmail.com.
Jean-Pierre A KocherDivision of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. kocher.jeanpierre@mayo.edu.
Andreas S BeutlerDepartment of Medical Oncology, Mayo Clinic, Rochester, MN, 55905, USA. beutler.andreas@mayo.edu.
Zhifu SunDivision of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, 55905, USA. sun.zhifu@mayo.edu.
Mayo Clinic · USMayo Clinic in Arizona · US

Funding

DNA Methylation Profiling of Chronic PainR21NS062271 · NINDS · MAYO CLINIC ROCHESTER · PI BEUTLER, ANDREAS S. · 2009 to 2010
$403k
NINDS NIH HHS 1R21NS062271NINDS NIH HHS R21 NS062271
6 · The paper itself

Abstract

backgroundDNA methylation is an important epigenetic modification involved in many biological processes. Reduced representation bisulfite sequencing (RRBS) is a cost-effective method for studying DNA methylation at single base resolution. Although several tools are available for RRBS data processing and analysis, it is not clear which strategy performs the best and there has not been much attention to the contamination issue from artificial cytosines incorporated during the end repair step of library preparation. To address these issues, we describe a new method, Targeted Alignment and Artificial Cytosine Elimination for RRBS (TRACE-RRBS), which aligns bisulfite sequence reads to MSP1 digitally digested reference and specifically removes the end repair cytosines. We compared this approach on a simulated and a real dataset with 7 other RRBS analysis tools and Illumina 450 K microarray platform.

resultsTRACE-RRBS aligns sequence reads to a small fraction of the genome where RRBS protocol targets on and was demonstrated as the fastest, most sensitive and specific tool for the simulated dataset. For the real dataset, TRACE-RRBS took about the same time as RRBSMAP, a third to a sixth of time needed for BISMARK and NOVOALIGN. TRACE-RRBS aligned more reads uniquely than other tools and achieved the highest correlation with 450 k microarray data. The end repair artificial cytosine removal increased correlation between nearby CpGs and accuracy of methylation quantification.

conclusionsTRACE-RRBS is fast and more accurate tool for RRBS data analysis. It is freely available for academic use at http://bioinformaticstools.mayo.edu/.

Indexed as

CytosineDNA MethylationEpigenesis, GeneticAlgorithmsCpG IslandsGenomicsHumansPolymorphism, Single NucleotideSequence AlignmentSequence Analysis, DNACytosine

Identifiers

PMID26922377
PMCPMC4769831
OpenAlexW2279505904

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.