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SigTools: Exploratory Visualization for Genomic Signals

Shohre Masoumi, Maxwell W. Libbrecht, Kay C. Wiese
doi: https://doi.org/10.1101/2021.08.02.454408
Shohre Masoumi
1Simon Fraser University, School of Computing Science
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Maxwell W. Libbrecht
1Simon Fraser University, School of Computing Science
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Kay C. Wiese
1Simon Fraser University, School of Computing Science
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  • For correspondence: wiese@sfu.ca
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Abstract

Motivation With the advancement of sequencing technologies, genomic data sets are constantly being expanded by high volumes of different data types. One recently introduced data type in genomic science is genomic signals, which are usually short-read coverage measurements over the genome. An example of genomic signals is Epigenomic marks which are utilized to locate functional and nonfunctional elements in genome annotation studies. To understand and evaluate the results of such studies, one needs to understand and analyze the characteristics of the input data.

Results SigTools is an R-based genomic signals visualization package developed with two objectives: 1) to facilitate genomic signals exploration in order to uncover insights for later model training, refinement, and development by including distribution and autocorrelation plots. 2) to enable genomic signals interpretation by including correlation, and aggregation plots. Moreover, Sigtools also provides text-based descriptive statistics of the given signals which can be practical when developing and evaluating learning models. We also include results from 2 case studies. The first examines several previously studied genomic signals called histone modifications. This use case demonstrates how SigTools can be beneficial for satisfying scientists’ curiosity in exploring and establishing recognized datasets. The second use case examines a dataset of novel chromatin state features which are novel genomic signals generated by a learning model. This use case demonstrates how SigTools can assist in exploring the characteristics and behavior of novel signals towards their interpretation. In addition, our corresponding web application, SigTools-Shiny, extends the accessibility scope of these modules to people who are more comfortable working with graphical user interfaces instead of command-line tools.

Availability SigTools source code, installation guide, and manual is available on http://github.com/shohre73.

Contact shohre_masoumi{at}sfu.ca

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted August 03, 2021.
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SigTools: Exploratory Visualization for Genomic Signals
Shohre Masoumi, Maxwell W. Libbrecht, Kay C. Wiese
bioRxiv 2021.08.02.454408; doi: https://doi.org/10.1101/2021.08.02.454408
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SigTools: Exploratory Visualization for Genomic Signals
Shohre Masoumi, Maxwell W. Libbrecht, Kay C. Wiese
bioRxiv 2021.08.02.454408; doi: https://doi.org/10.1101/2021.08.02.454408

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