Evidence map›Paper›PMID 34044763›Full record

ArticleBMC bioinformatics2021

An effective method to resolve ambiguous bisulfite-treated reads.

Mengya Liu, Yun Xu

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

2 authors.

Mengya LiuSchool of Computer Science, University of Science and Technology of China, Hefei, 230027, Anhui, China.
Yun XuSchool of Computer Science, University of Science and Technology of China, Hefei, 230027, Anhui, China. xuyun@ustc.edu.cn.

Funding

the Fund for Foreign Scholars in University Research and Teaching Programs B07033the National Nature Science Foundation of China No. 61672480
6 · The paper itself

Abstract

backgroundThe combination of the bisulfite treatment and the next-generation sequencing is an important method for methylation analysis, and aligning the bisulfite-treated reads (BS-reads) is the critical step for the downstream applications. As bisulfite treatment reduces the complexity of the sequences, a large portion of BS-reads might be aligned to multiple locations of the reference genome ambiguously, called multireads. These multireads cannot be employed in the downstream applications since they are likely to introduce artifacts. To identify the best mapping location of each multiread, existing Bayesian-based methods calculate the probability of the read at each position by considering how does it overlap with unique mapped reads. However, [Formula: see text]% of multireads are not overlapped with any unique reads, which are unresolvable for existing method.

resultsHere we propose a novel method (EM-MUL) that not only rescues multireads overlapped with unique reads, but also uses the overall coverage and accurate base-level alignment to resolve multireads that cannot be handled by current methods. We benchmark our method on both simulated datasets and real datasets. Experimental results show that it is able to align more than 80% of multireads to the best mapping position with very high accuracy.

conclusionsEM-MUL is an effective method designed to accurately determine the best mapping position of multireads in BS-reads. For the downstream applications, it is useful to improve the methylation resolution on the repetitive regions of genome. EM-MUL is free available at https://github.com/lmylynn/EM-MUL.

Indexed as

SoftwareSulfitesBayes TheoremDNA MethylationHigh-Throughput Nucleotide SequencingSequence Analysis, DNAhydrogen sulfiteSulfitesBisulfiteDNAMethylationMultireads

Identifiers

PMID34044763
PMCPMC8161933

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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.