Correspondance of myTAI and orthomap functions
myTAI::TAI() in R
install.packages("myTAI")
library(myTAI)
data(PhyloExpressionSetExample)
TAI(PhyloExpressionSetExample)
orthomap2tei.get_tei() in Python
import scanpy as sc
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from orthomap import of2orthomap, orthomap2tei, datasets
adata = datasets.mytai_example(datapath='.')
orthomap2tei.get_tei(
adata=adata,
gene_id=adata.var.index,
gene_age=adata.var['Phylostrata'])
myTAI::PlotDistribution() in R
PlotDistribution(PhyloExpressionSetExample)
of2orthomap.get_counts_per_ps() in Python
query_orthomap = pd.DataFrame(adata.var.index,
columns=['GeneID'])
query_orthomap['Phylostrata']=adata.var['Phylostrata'].values
of2orthomap.get_counts_per_ps(omap_df=query_orthomap,
psnum_col='Phylostrata',
pstaxid_col=None,
psname_col=None).plot.bar(y='counts', x='Phylostrata')
plt.show()
myTAI::REMatrix() and myTAI::PlotRE() in R
REMatrix(PhyloExpressionSetExample)
PlotRE(PhyloExpressionSetExample, Groups=list(1:12))
orthomap2tei.get_rematrix() in Python
rematrix = orthomap2tei.get_rematrix(
adata=adata,
gene_id=adata.var.index,
gene_age=adata.var['Phylostrata'],
standard_scale=0)
rematrix.transpose().plot.line(cmap='Accent')
plt.show()
myTAI::pStrata() and myTAI::PlotContribution() in R
pstrata <- pStrata(PhyloExpressionSetExample)
PlotContribution(PhyloExpressionSetExample, "PS")
orthomap2tei.get_pstrata() in Python
pstrata = orthomap2tei.get_pstrata(
adata=adata,
gene_id=adata.var.index,
gene_age=adata.var['Phylostrata'])
pstrata[0]
pstrata[0].transpose().plot.line(cmap='Accent', stacked=True)
plt.show()
myTAI::pMatrix() in R
pmatrix <- pMatrix(PhyloExpressionSetExample)
pmatrix
boxplot(pmatrix, outline=FALSE)
orthomap2tei.get_pmatrix() in Python
pmatrix = orthomap2tei.get_pmatrix(
adata=adata,
gene_id=adata.var.index,
gene_age=adata.var['Phylostrata'])
pd.DataFrame(pmatrix.layers['pmatrix'].toarray(),
index=pmatrix.obs.index).transpose().boxplot(showfliers=False)
plt.show()
myTAI::PlotGeneSet() in R
marker_expression <- PlotGeneSet(ExpressionSet = PhyloExpressionSetExample,
gene.set = PhyloExpressionSetExample[1:5, 2],
get.subset = TRUE)
PlotGeneSet(ExpressionSet = PhyloExpressionSetExample,
gene.set = PhyloExpressionSetExample[1:5, 2])
scanpy in Python
marker_genes = adata.var_names[:5]
marker_expression = pd.DataFrame(adata[:, marker_genes].X.toarray(),
columns=marker_genes, index=adata.obs.index)
marker_expression.plot.line(cmap='Accent')
plt.show()
myTAI::PlotMeans() in R
PlotMeans(PhyloExpressionSetExample, Groups=list(1:12))
orthomap2tei.get_ematrix() in Python
ematrix = orthomap2tei.get_ematrix(
adata=adata,
group_by_var='Phylostrata')
ematrix.transpose().plot.line(cmap='Accent')
plt.show()