Description Usage Arguments Details Author(s) See Also Examples
View source: R/BI_boxplot_genedata.R
boxplot_genedata provide fast way to draw boxplot for gene expression based on gene expression matrix and design object
1 2 3 4 5 6 | boxplot_genedata(select.genes, design, expr.matrix, convert = T,
type = c("facet", "normal")[1], contrast = "N.status",
contrast.list = c("N0", "Np"), genes.levels = NULL, palette = NULL,
point.alpha = 0.5, box.alpha = 1, method = "wilcox.test",
x.title = NULL, y.title = NULL, legend.position = c(0.9, 0.9),
cut = F, ncut = 2, width = 12, height = 10, names = "love")
|
select.genes |
the genes you want to plot |
design |
the design object(data of clinical features) |
expr.matrix |
expression matrix of genes |
convert |
Whether to convert Ensembl id as symbols.Default is |
type |
the style of boxplot.One of "facet" and "normal". |
contrast |
the colnames of contrast value.Like "N.status". |
contrast.list |
the components of contrast.Like c("N0","Np") |
genes.levels |
the level of genes.Default is NULL,and it's recommanded that you set a self-defined levels for better visualization. |
palette |
the color of genes ploted.Default is NULL. |
point.alpha |
the color density of point |
box.alpha |
the color density of box |
method |
the method of P value for comparision.Default is "wilcox.test".See also |
x.title |
the names of x axis of plot |
y.title |
the names of y axis of plot |
cut |
whether to cut plot.If the number of genes is very much,it is recommanded to set |
ncut |
the number of cut strategy.Only available when |
width |
the width of plot |
height |
the height of plot |
names |
part name of the saved plot |
the names of genes shold be Ensembl id.
Weibin Huang<654751191@qq.com>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | library(lucky)
data("rna.tpm",package = "lucky")
data("rna.design",package = "lucky")
p <- boxplot_genedata(select.genes = c("ENSG00000004478",
"ENSG00000000457"),
design = rna.design,
expr.matrix = log2(rna.tpm + 1),
contrast = "condition",
contrast.list = c("normal","tumor"),
genes.levels = NULL,
palette=NULL,
point.alpha = 0.5,
box.alpha = 1,
method = "wilcox.test",
x.title="Genes",
y.title="The Expression of Genes(log TPM)",
cut = F,
width = 12,height = 10,
names = "love")
## See plot of genes expression
print(p$plot)
## See meta data of genes expression
View(p$metadata)
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