Xiuquan Wang, Mian Umair Ahsan, Yunyun Zhou, Kai Wang
Background : Oxford Nanopore long-read sequencing technology addresses current limitations for DNA methylation detection that are inherent in short-read bisulfite sequencing or methylation microarrays. A number of analytical tools, such as Nanopolish, Guppy/Tombo and DeepMod, have been developed to detect DNA methylation on Nanopore data. However, additional improvements can be made in computational efficiency, prediction accuracy, and contextual interpretation on complex genomics regions (such as repetitive regions, low GC density regions). Method : In the current study, we apply Transformer architecture to detect DNA methylation on ionic signals from Oxford Nanopore sequencing data. Transformer is an algorithm that adopts self-attention architecture in the neural networks and has been widely used in natural language processing. Results : Compared to traditional deep-learning method such as convolutional neural network (CNN) and recurrent neural network (RNN), Transformer may have specific advantages in DNA methylation detection, because the self-attention mechanism can assist the relationship detection between bases that are far from each other and pay more attention to important bases that carry characteristic methylation-specific signals within a specific sequence context. Conclusion : We demonstrated the ability of Transformers to detect methylation on ionic signal data.
{"title":"Transformer-based DNA methylation detection on ionic signals from Oxford Nanopore sequencing data","authors":"Xiuquan Wang, Mian Umair Ahsan, Yunyun Zhou, Kai Wang","doi":"10.15302/j-qb-022-0323","DOIUrl":"https://doi.org/10.15302/j-qb-022-0323","url":null,"abstract":"Background : Oxford Nanopore long-read sequencing technology addresses current limitations for DNA methylation detection that are inherent in short-read bisulfite sequencing or methylation microarrays. A number of analytical tools, such as Nanopolish, Guppy/Tombo and DeepMod, have been developed to detect DNA methylation on Nanopore data. However, additional improvements can be made in computational efficiency, prediction accuracy, and contextual interpretation on complex genomics regions (such as repetitive regions, low GC density regions). Method : In the current study, we apply Transformer architecture to detect DNA methylation on ionic signals from Oxford Nanopore sequencing data. Transformer is an algorithm that adopts self-attention architecture in the neural networks and has been widely used in natural language processing. Results : Compared to traditional deep-learning method such as convolutional neural network (CNN) and recurrent neural network (RNN), Transformer may have specific advantages in DNA methylation detection, because the self-attention mechanism can assist the relationship detection between bases that are far from each other and pay more attention to important bases that carry characteristic methylation-specific signals within a specific sequence context. Conclusion : We demonstrated the ability of Transformers to detect methylation on ionic signal data.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High-throughput metabarcoding of SAR11 assemblages from the southwest Atlantic shelf and arid Patagonia: richness and as-sociated rank abundance distributions","authors":"","doi":"10.15302/j-qb-023-0329","DOIUrl":"https://doi.org/10.15302/j-qb-023-0329","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Building digital life systems for future biology and medicine","authors":"","doi":"10.15302/j-qb-023-0331","DOIUrl":"https://doi.org/10.15302/j-qb-023-0331","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Secure and efficient implementation of facial emotion detection for smart patient monitoring system","authors":"","doi":"10.15302/j-qb-022-0312","DOIUrl":"https://doi.org/10.15302/j-qb-022-0312","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pattern discovery of long non-coding RNAs associated with the herbal treatments in breast and prostate cancers","authors":"","doi":"10.15302/j-qb-023-0333","DOIUrl":"https://doi.org/10.15302/j-qb-023-0333","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Light-driven synthetic microbial consortia: playing with an oxygen dilemma","authors":"","doi":"10.15302/j-qb-022-0314","DOIUrl":"https://doi.org/10.15302/j-qb-022-0314","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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