Description Usage Arguments Value Examples
plotStaircase
Function to plot heatmap for genes-sample pairs orderd by genes which explain most of the patients .
1 2 3 4 |
sample.mutations |
data frame in MAF like format.
Columns (with exactly same names) which
|
result.df |
a data frame with Hugo_Symbol column. Genes in this column should be ordered by importance. |
topGenes |
a numeric/integer value; How meny top genes from results will be ploted. |
silent |
a boolean value indicating should silent mutations be counted. By default it is True. |
indels |
a boolean value indicating should indels be counted. By default it is True. |
allSamples |
a boolean value indicating if all samples should be plotted. |
Tumor_Sample_Barcode |
(optional) integer/numeric value indicating column in |
Hugo_Symbol |
(optional) integer/numeric value indicating column in |
Variant_Classification |
(optional) integer/numeric value indicating column in |
Variant_Type |
(optional) integer/numeric value indicating column in |
color |
a numeric or character value indicating column to color the samples. |
groupMax |
a numeric value which will be taken as maximum value when grouping color column for samples and genes pairs. |
order |
a character value which can be or |
ggplot2 object
1 2 3 4 5 6 7 8 9 10 | #get CCF column
sample.genes.mutect <- CCF(sample.genes.mutect)
# get background
bcgr.prob <- bcgr.combine(sample.genes.mutect)
# get ranking
df1 <- bayes.risk(sample.genes.mutect, bcgr.prob, prior.sick = 0.00007)
df2 <- bayes.driver(sample.genes.mutect, bcgr.prob, prior.driver = 0.001)
df.final <- combine.ranking(list(df1, df2), min.mut = 2 )
# plot boxplot of CCF for top genes
plotStaircase(sample.mutations=sample.genes.mutect, result.df=df.final)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.