2021
DOI: 10.3389/fgene.2021.774846
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Use ggbreak to Effectively Utilize Plotting Space to Deal With Large Datasets and Outliers

Abstract: With the rapid increase of large-scale datasets, biomedical data visualization is facing challenges. The data may be large, have different orders of magnitude, contain extreme values, and the data distribution is not clear. Here we present an R package ggbreak that allows users to create broken axes using ggplot2 syntax. It can effectively use the plotting area to deal with large datasets (especially for long sequential data), data with different magnitudes, and contain outliers. The ggbreak package increases … Show more

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Cited by 142 publications
(83 citation statements)
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“…Plotting and statistical analysis were performed in the R coding environment (R Core Team, 2017; Xu et al, 2021)…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Plotting and statistical analysis were performed in the R coding environment (R Core Team, 2017; Xu et al, 2021)…”
Section: Discussionmentioning
confidence: 99%
“…Plotting and statistical analysis were performed in the R coding environment (R Core Team, 2017; Xu et al, 2021). All data was assessed for normality and homogeneity of variances prior to selecting the statistical test.…”
Section: Methodsmentioning
confidence: 99%
“…Canonical pathways (reactome) gene set for gene set enrichment analysis was retrieved using the msigdbr R package v.7.4.1. Other R packages used to analyze and visualize RNA-seq data include tidyverse v.1.3.1 ( 89 ), cowplot v.1.1.1, ggbreak v.0.0.9 ( 90 ), ggrepel v.0.9.1, RColorBrewer v.1.1-2, gplots v.3.1.3, and enrichplot v.1.14.2 with scripts from DIY.transcriptomics ( 91 ).…”
Section: Methodsmentioning
confidence: 99%
“…OPAL (commit edb6f41 in dev branch) [29] is used to assess taxonomic metagenome profilers. R 4.1.2 [57], ggplot2 3.3.5 [58], ggbreak 0.0.9 [59], and some other R packages are used for data visualization.…”
Section: Methodsmentioning
confidence: 99%