henhaobio
Sign in

BMC GenomicsBioinformaticsPeer-reviewed journal article

Sequoia: An interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

Ratanond KoonchanokiD, Swapna Vidhur DaulatabadiD, Quoseena MiriD, Khairi RedaiD, Sarath Chandra JangaiD

PDFDOIPreprint

Abstract

Sequoia is a visualization tool that allows biologists to explore characteristics of signals generated by the Oxford Nanopore Technologies (ONT) in detail. From Fast5 files generated by ONT, the tool displays relative similarities between signals using the dynamic time warping and the t-SNE algorithms. Raw signals can be visualized through mouse actions while particular signals of interest can also be exported as a CSV file for further analysis. Sequoia consists of two major components: the command-line back-end that performs necessary computations using Python and the front-end that displays the visualization through a web interface. Two datasets are used to conduct a case study in order to illustrate the usability of the tool.

Citations
4
FWCI
0.16
Field percentile
38th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSamarakoon '24Loman '14Bolognini '19Ferguson '19Bruno '21Wierczeiko '23
78% semantic matchBioinformatics
Hiruna Samarakoon, Kisaru Liyanage, James M. Ferguson+3 more·bioRxiv·Feb 19, 2024· 5 citations