Journal
BMC BIOINFORMATICS
Volume 22, Issue 1, Pages -Publisher
BMC
DOI: 10.1186/s12859-021-04204-6
Keywords
DNA; Methylation; Bisulfite; Multireads
Categories
Funding
- National Nature Science Foundation of China [61672480]
- Fund for Foreign Scholars in University Research and Teaching Programs [B07033]
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The novel method EM-MUL proposed in this study can effectively resolve the issue of multireads in BS-reads, with experimental results showing high accuracy and efficiency in aligning multireads.
Background: The combination of the bisulfite treatment and the next-generation sequencing is an important method for methylation analysis, and aligning the bisulfitetreated 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, similar to 25% of multireads are not overlapped with any unique reads, which are unresolvable for existing method. Results: Here 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. Conclusions: EM-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.comilmylynn/EM-MUL.
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