Evidence map›Paper›PMID 31842729›Full record

ArticleBMC bioinformatics2019

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

Chandler D Gatenbee, Ryan O Schenck, Rafael R Bravo, Alexander R A Anderson

Abstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chandler D GatenbeeIntegrated Mathematical Oncology, Moffitt Cancer Center, Tampa, 33612, FL, USA.
Ryan O SchenckIntegrated Mathematical Oncology, Moffitt Cancer Center, Tampa, 33612, FL, USA.
Rafael R BravoIntegrated Mathematical Oncology, Moffitt Cancer Center, Tampa, 33612, FL, USA.
Alexander R A AndersonIntegrated Mathematical Oncology, Moffitt Cancer Center, Tampa, 33612, FL, USA. Alexander.Anderson@moffitt.org.ORCID http://orcid.org/0000-0002-2536-4383

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh 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.

resultsHere 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.

conclusionsEvoFreq, 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.

Indexed as

High-Throughput Nucleotide SequencingBiological EvolutionGenotypeSoftwareEvolutionTumorVisualization software

Identifiers

PMID31842729
PMCPMC6916070

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.