dotools_py.pl.volcano_plot

dotools_py.pl.volcano_plot(df, lfc_col='log2fc', pval_col='padj', gene_col='GeneName', figsize=(7, 5), ax=None, title='', legend_loc='right', legend_ncols=1, path=None, filename='Volcano.svg', show=True, pval_lim=2e-10, lfc_lim=(-6, 6), lfc_cut=0.25, pval_cut=0.05, mygenes=None, clean=True, dot_size=3, topn=10, textprops=None, **kwargs)

Generate a volcano plot.

Genes will be colored differently depending on the p-value (Pval) and logfoldchange (LFC):

• Genes Pval < pval_cut & LFC > lfc_cut: Red.

• Genes Pval < pval_cut & LFC < lfc_cut: Blue.

• Genes Pval > pval_cut & LFC > lfc_cut: Green.

• Genes Pval > pval_cut & LFC < lfc_cut: Gray.

If no genes are provided (mygenes) the top 10 genes with highest and lowest LFC that are significant will be indicated.

Parameters:

df DataFrame

pandas dataframe with DGE. Should have at least 3 columns (Genes, Pvalue, Logfoldchange).

lfc_col str (default: 'log2fc')

name of the column that has the logfoldchanges.

pval_col str (default: 'padj')

name of the column that has the Pvals.

gene_col str (default: 'GeneName')

name of the column that has the gene names.

path str | PathLike[str] | Path (default: None)

path where to save the figure.

filename str (default: 'Volcano.svg')

name of the file.

pval_lim float (default: 2e-10)

Y-axis limit. Genes with a < p-value will be set to this value.

lfc_lim tuple (default: (-6, 6))

X-axis limit. Genes with a > LFC will be ignored.

title str (default: '')

a text to add as the title of the plot.

figsize tuple[int, int] (default: (7, 5))

size of the plot.

ax Axes (default: None)

matplotlib axis.

legend_loc Literal['top', 'bottom', 'right'] (default: 'right')

location of the legend.

legend_ncols int (default: 1)

number of columns for the legend.

lfc_cut float (default: 0.25)

significance threshold for the LFC.

pval_cut float (default: 0.05)

significance threshold for the P-value.

mygenes list | None (default: None)

list of genes to be annotated.

clean bool (default: True)

remove genes with Pval == 1 and LFC > lfc_lim.

dot_size float (default: 3)

size of the dots.

topn int (default: 10)

if mygenes is None. The top 10 positive and negative genes are plotted.

textprops dict (default: None)

properties of the gene labels (See plt.text)

show bool (default: True)

if set to true, return axis.

Return type:

dict | None

Returns:

Depending on show, returns the plot if set to True or a dictionary with the axes.

Example

import dotools_py as do
adata = do.dt.example_10x_processed()
do.tl.rank_genes_groups(adata,  'condition', method='wilcoxon', tie_correct=True, pts=True)
table = do.get.dge_results(adata)
table = table[table.group == 'disease']
do.pl.volcano_plot(table, 'log2fc', 'padj', 'GeneName')