Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.

Nanopore sequencing device analysis systems simultaneously generate multiple picoamperage current signals representing the passage of DNA or RNA nucleotides ratcheted through a biomolecule nanopore array by motor proteins. Squiggles are a noisy and time-distorted representation of an underlying nucl...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Michael Smith, Rachel Chan, Maaz Khurram, Paul M K Gordon
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/c93dfe1860d04d21b65897a745226eb3
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:c93dfe1860d04d21b65897a745226eb3
record_format	dspace
spelling	oai:doaj.org-article:c93dfe1860d04d21b65897a745226eb32021-12-02T19:57:49ZEvaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.1553-734X1553-735810.1371/journal.pcbi.1009350https://doaj.org/article/c93dfe1860d04d21b65897a745226eb32021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009350https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Nanopore sequencing device analysis systems simultaneously generate multiple picoamperage current signals representing the passage of DNA or RNA nucleotides ratcheted through a biomolecule nanopore array by motor proteins. Squiggles are a noisy and time-distorted representation of an underlying nucleotide sequence, "gold standard model", due to experimental and algorithmic artefacts. Other research fields use dynamic time warped-space averaging (DTWA) algorithms to produce a consensus signal from multiple time-warped sources while preserving key features distorted by standard, linear-averaging approaches. We compared the ability of DTW Barycentre averaging (DBA), minimize mean (MM) and stochastic sub-gradient descent (SSG) DTWA algorithms to generate a consensus signal from squiggle-space ensembles of RNA molecules Enolase, Sequin R1-71-1 and Sequin R2-55-3 without knowledge of their associated gold standard model. We propose techniques to identify the leader and distorted squiggle features prior to DTWA consensus generation. New visualization and warping-path metrics are introduced to compare consensus signals and the best estimate of the "true" consensus, the study's gold standard model. The DBA consensus was the best match to the gold standard for both Sequin studies but was outperformed in the Enolase study. Given an underlying common characteristic across a squiggle ensemble, we objectively evaluate a novel "voting scheme" that improves the local similarity between the consensus signal and a given fraction of the squiggle ensemble. While the gold standard is not used during voting, the increase in the match of the final voted-on consensus to the underlying Enolase and Sequin gold standard sequences provides an indirect success measure for the proposed voting procedure in two ways: First is the decreased least squares warped distance between the final consensus and the gold model, and second, the voting generates a final consensus length closer to the known underlying RNA biomolecule length. The results suggest considerable potential in marrying squiggle analysis and voted-on DTWA consensus signals to provide low-noise, low-distortion signals. This will lead to improved accuracy in detecting nucleotides and their deviation model due to chemical modifications (a.k.a. epigenetic information). The proposed combination of ensemble voting and DTWA has application in other research fields involving time-distorted, high entropy signals.Michael SmithRachel ChanMaaz KhurramPaul M K GordonPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009350 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Michael Smith Rachel Chan Maaz Khurram Paul M K Gordon Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
description	Nanopore sequencing device analysis systems simultaneously generate multiple picoamperage current signals representing the passage of DNA or RNA nucleotides ratcheted through a biomolecule nanopore array by motor proteins. Squiggles are a noisy and time-distorted representation of an underlying nucleotide sequence, "gold standard model", due to experimental and algorithmic artefacts. Other research fields use dynamic time warped-space averaging (DTWA) algorithms to produce a consensus signal from multiple time-warped sources while preserving key features distorted by standard, linear-averaging approaches. We compared the ability of DTW Barycentre averaging (DBA), minimize mean (MM) and stochastic sub-gradient descent (SSG) DTWA algorithms to generate a consensus signal from squiggle-space ensembles of RNA molecules Enolase, Sequin R1-71-1 and Sequin R2-55-3 without knowledge of their associated gold standard model. We propose techniques to identify the leader and distorted squiggle features prior to DTWA consensus generation. New visualization and warping-path metrics are introduced to compare consensus signals and the best estimate of the "true" consensus, the study's gold standard model. The DBA consensus was the best match to the gold standard for both Sequin studies but was outperformed in the Enolase study. Given an underlying common characteristic across a squiggle ensemble, we objectively evaluate a novel "voting scheme" that improves the local similarity between the consensus signal and a given fraction of the squiggle ensemble. While the gold standard is not used during voting, the increase in the match of the final voted-on consensus to the underlying Enolase and Sequin gold standard sequences provides an indirect success measure for the proposed voting procedure in two ways: First is the decreased least squares warped distance between the final consensus and the gold model, and second, the voting generates a final consensus length closer to the known underlying RNA biomolecule length. The results suggest considerable potential in marrying squiggle analysis and voted-on DTWA consensus signals to provide low-noise, low-distortion signals. This will lead to improved accuracy in detecting nucleotides and their deviation model due to chemical modifications (a.k.a. epigenetic information). The proposed combination of ensemble voting and DTWA has application in other research fields involving time-distorted, high entropy signals.
format	article
author	Michael Smith Rachel Chan Maaz Khurram Paul M K Gordon
author_facet	Michael Smith Rachel Chan Maaz Khurram Paul M K Gordon
author_sort	Michael Smith
title	Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
title_short	Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
title_full	Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
title_fullStr	Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
title_full_unstemmed	Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.
title_sort	evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various dtwa algorithms from step-current signals generated during nanopore sequencing.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/c93dfe1860d04d21b65897a745226eb3
work_keys_str_mv	AT michaelsmith evaluatingtheeffectivenessofensemblevotinginimprovingtheaccuracyofconsensussignalsproducedbyvariousdtwaalgorithmsfromstepcurrentsignalsgeneratedduringnanoporesequencing AT rachelchan evaluatingtheeffectivenessofensemblevotinginimprovingtheaccuracyofconsensussignalsproducedbyvariousdtwaalgorithmsfromstepcurrentsignalsgeneratedduringnanoporesequencing AT maazkhurram evaluatingtheeffectivenessofensemblevotinginimprovingtheaccuracyofconsensussignalsproducedbyvariousdtwaalgorithmsfromstepcurrentsignalsgeneratedduringnanoporesequencing AT paulmkgordon evaluatingtheeffectivenessofensemblevotinginimprovingtheaccuracyofconsensussignalsproducedbyvariousdtwaalgorithmsfromstepcurrentsignalsgeneratedduringnanoporesequencing
_version_	1718375804358885376

Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.

Ejemplares similares