plotMa | R Documentation |
The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales.
plotMa(object, ...)
## S4 method for signature 'DESeqAnalysis'
plotMa(
object,
i,
alphaThreshold = NULL,
baseMeanThreshold = NULL,
lfcThreshold = NULL,
genes = NULL,
ntop = 0L,
...
)
## S4 method for signature 'DESeqResults'
plotMa(
object,
direction = c("both", "up", "down"),
alphaThreshold = NULL,
baseMeanThreshold = NULL,
lfcThreshold = NULL,
genes = NULL,
ntop = 0L,
pointColor = c(downregulated = AcidPlots::lightPalette[["purple"]], upregulated =
AcidPlots::lightPalette[["orange"]], nonsignificant =
AcidPlots::lightPalette[["gray"]]),
pointSize = 2L,
pointAlpha = 0.8,
limits = list(x = NULL, y = NULL),
labels = list(title = TRUE, subtitle = NULL)
)
object |
Object. |
i |
Indices specifying elements to extract or replace. Indices are For more information: help(topic = "Extract", package = "base") |
alphaThreshold |
|
baseMeanThreshold |
|
lfcThreshold |
|
genes |
|
ntop |
|
... |
Additional arguments. |
direction |
|
pointColor |
|
pointSize |
|
pointAlpha |
|
limits |
|
labels |
|
An MA plot is an application of a Bland–Altman plot for visual representation of genomic data. The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values.
ggplot
.
plotMa(DESeqAnalysis)
: Passes to DESeqResults
method, with gene2symbol
argument automatically defined.
Updated 2022-03-08.
Michael Steinbaugh, Rory Kirchner
DESeq2::plotMA()
.
data(deseq)
## Get genes from DESeqDataSet.
dds <- as(deseq, "DESeqDataSet")
genes <- head(rownames(dds))
print(genes)
## DESeqAnalysis ====
plotMa(deseq, i = 1L)
## Customize the colors.
plotMa(
object = deseq,
i = 1L,
pointColor = c(
downregulated = "red",
nonsignificant = "black",
upregulated = "green"
)
)
## Directional support (up or down).
plotMa(deseq, i = 1L, direction = "up", ntop = 5L)
plotMa(deseq, i = 1L, direction = "down", ntop = 5L)
## Label genes manually.
## Note that either gene IDs or names (symbols) are supported.
plotMa(deseq, i = 1L, genes = genes)
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