Plot Gene Expression with Automatic Statistical Analysis

Generates an annotated visualization of gene expression between two groups. For a single-gene data frame, the plot is annotated with statistical results from analyze.gene(). For a multi-gene data frame, the plot is faceted by gene and annotations are omitted, use analyze.gene() on each gene subset for per-gene statistics.

Usage

gene.analysis.plot(df, alpha = 0.05, n.boot = 1000, show.points = TRUE)

Arguments

df

A data frame as produced by build.analysis.df(), containing:

expression: Numeric vector of gene expression values.
group: Character or factor vector with exactly two group labels.
gene: Character vector of gene names. Optional; when present and containing more than one unique value, enables faceted multi-gene plotting.

alpha

Numeric. Significance level passed to analyze.gene(). Default is 0.05. Only used in single-gene mode.

n.boot

Integer. Number of bootstrap resamples for the confidence interval, passed to analyze.gene(). Default is 1000. Only used in single-gene mode.

show.points

Logical. Whether to overlay jittered individual sample points on the violin/boxplot. Default is TRUE.

Value

A ggplot object. In single-gene mode the plot includes a text annotation with p-value, Cohen's d, and bootstrapped CI, and a subtitle with the full interpretation string. In multi-gene mode the plot is faceted by gene with no statistical annotation.

Details

Single-gene mode is triggered when the gene column is absent or contains exactly one unique value. Multi-gene mode is triggered when gene contains more than one unique value, producing a facet_wrap(~ gene) layout. The plot theme is consistent across both modes and matches the style conventions of the BioUtils package.

Examples

# \donttest{
geo <- extract.expression(load.geo.soft(accession = "GDS3268", log.transform = TRUE))
#> GDS3268 not found locally, downloading from NCBI GEO...
#> Using locally cached version of GDS3268 found here:
#> /tmp/RtmpxRZSjV/GDS3268.soft.gz 
#> Warning: NaNs produced
#> Using locally cached version of GPL1708 found here:
#> /tmp/RtmpxRZSjV/GPL1708.annot.gz 

# Single-gene plot with statistical annotation
probe <- find.probe.by.gene(geo$gene, "mucin 20, cell surface associated")
expr <- get.gene.expression(geo$expression, probe)
df <- build.analysis.df(expr, geo$phenotype, geo$gene)
gene.analysis.plot(df)


# Multi-gene faceted plot
probes <- find.probe.by.gene(geo$gene, c(
  "mucin 20, cell surface associated",
  "alcohol dehydrogenase 1A (class I), alpha polypeptide"
))
expr.multi <- get.gene.expression(geo$expression, probes)
df.multi <- build.analysis.df(expr.multi, geo$phenotype, geo$gene)
gene.analysis.plot(df.multi)

# }