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. 2019 Dec 16;20(1):710.
doi: 10.1186/s12859-019-3173-y.

EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data

Chandler D Gatenbee  1 , Ryan O Schenck  1   2 , Rafael R Bravo  1 , Alexander R A Anderson  3
Affiliations

EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data

Chandler D Gatenbee et al. BMC Bioinformatics. .

Abstract

Background: High throughput sequence data has provided in depth means of molecular characterization of populations. When recorded at numerous time steps, such data can reveal the evolutionary dynamics of the population under study by tracking the changes in genotype frequencies over time. This necessitates a simple and flexible means of visualizing an increasingly complex set of data.

Results: Here we offer EvoFreq as a comprehensive tool set to visualize the evolutionary and population frequency dynamics of clones at a single point in time or as population frequencies over time using a variety of informative methods. EvoFreq expands substantially on previous means of visualizing the clonal, temporal dynamics and offers users a range of options for displaying their sequence or model data.

Conclusions: EvoFreq, implemented in R with robust user options and few dependencies, offers a high-throughput means of quickly building, and interrogating the temporal dynamics of hereditary information across many systems. EvoFreq is freely available via https://github.com/MathOnco/EvoFreq.

Keywords: Evolution; Tumor; Visualization software.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
EvoFreq is a comprehensive and flexible R package for the visualization of longitudinal data. a and b show an EvoFreq plot for one of the provided datasets with b and without a the function to add labels. For more complicated data EvoFreq provides a powerful means to quickly filter data (c and d thresholded at 0.2 frequency), color by an attribute (driver strength), and visualize dynamics as a frequencies rather than population size. Using a dendogram styled to ensure that origin time is easily conveyed (termed here as an EvoGram), a more quantitative view is provided e
Fig. 2
Fig. 2
EvoFreq can be easily used to visualize outputs from CloneEvol, PhyloWGS, and CALDER. Data parsing functions are included within EvoFreq to rapidly visualize subclonal reconstructions. Each column above illustrates a method of subclonal reconstruction for two separate human breast cancer xenograftments from Eirew et al. [6] for PhyloWGS (left) and CALDER (right). Originating tumors (T) and their subsequent xenograft passages (X1, X2, etc.) are shown for SA501 (top) and SA536 (bottom)
See this image and copyright information in PMC

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