In this paper we develop a theory describing how the extended Burrows-Wheeler Transform (eBWT) of a collection of DNA fragments tends to cluster together the copies of nucleotides sequenced from a genome G. Our theory accurately predicts how many copies of any nucleotide are expected inside each such cluster, and how an elegant and precise LCP array based procedure can locate these clusters in the eBWT. Our findings are very general and can be applied to a wide range of different problems. In this paper, we consider the case of alignment-free and reference-free SNPs discovery in multiple collections of reads. We note that, in accordance with our theoretical results, SNPs are clustered in the eBWT of the reads collection, and we develop a tool finding SNPs with a simple scan of the eBWT and LCP arrays. Preliminary results show that our method requires much less coverage than state-of-the-art tools while drastically improving precision and sensitivity.

Prezza, N., Pisanti, N., Sciortino, M., Rosone, G. (2018). Detecting mutations by eBWT. In L. Parida, E. Ukkonen (a cura di), 18th International Workshop on Algorithms in Bioinformatics (WABI 2018) (pp. 1-15). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.WABI.2018.3].

Detecting mutations by eBWT

Sciortino, Marinella;Rosone, Giovanna
2018-01-01

Abstract

In this paper we develop a theory describing how the extended Burrows-Wheeler Transform (eBWT) of a collection of DNA fragments tends to cluster together the copies of nucleotides sequenced from a genome G. Our theory accurately predicts how many copies of any nucleotide are expected inside each such cluster, and how an elegant and precise LCP array based procedure can locate these clusters in the eBWT. Our findings are very general and can be applied to a wide range of different problems. In this paper, we consider the case of alignment-free and reference-free SNPs discovery in multiple collections of reads. We note that, in accordance with our theoretical results, SNPs are clustered in the eBWT of the reads collection, and we develop a tool finding SNPs with a simple scan of the eBWT and LCP arrays. Preliminary results show that our method requires much less coverage than state-of-the-art tools while drastically improving precision and sensitivity.
2018
978-3-95977-082-8
Prezza, N., Pisanti, N., Sciortino, M., Rosone, G. (2018). Detecting mutations by eBWT. In L. Parida, E. Ukkonen (a cura di), 18th International Workshop on Algorithms in Bioinformatics (WABI 2018) (pp. 1-15). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing [10.4230/LIPIcs.WABI.2018.3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/337223
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