Pathway analysis

Setup

Reactome pathway

pi3ks=['PIK3CA','PIK3CB','PIK3CD','PIK3CG','PIK3R1','PIK3R2','PIK3R3','PTEN','AKT1','AKT2','AKT3','MTOR','RICTOR','RPTOR','TSC1','TSC2','PDK1','IRS1','IRS2','INSR','IGF1R','GAB1','HRAS','NRAS','KRAS','EGFR','ERBB2','ERBB3','ERBB4']

raw_out = get_reactome_raw(pi3ks)
raw_out.head()

	stId	dbId	name	llp	inDisease	species.dbId	species.taxId	species.name	entities.resource	entities.total	entities.found	entities.ratio	entities.pValue	entities.fdr	entities.exp	reactions.resource	reactions.total	reactions.found	reactions.ratio
0	R-HSA-1963640	1963640	GRB2 events in ERBB2 signaling	True	False	48887	9606	Homo sapiens	TOTAL	21	9	0.001301	1.110223e-16	1.221245e-15	[]	TOTAL	4	4	0.000252
1	R-HSA-9665348	9665348	Signaling by ERBB2 ECD mutants	True	True	48887	9606	Homo sapiens	TOTAL	23	9	0.001425	1.110223e-16	1.221245e-15	[]	TOTAL	15	15	0.000945
2	R-HSA-9664565	9664565	Signaling by ERBB2 KD Mutants	True	True	48887	9606	Homo sapiens	TOTAL	35	13	0.002168	1.110223e-16	1.221245e-15	[]	TOTAL	17	17	0.001071
3	R-HSA-1227990	1227990	Signaling by ERBB2 in Cancer	False	True	48887	9606	Homo sapiens	TOTAL	36	13	0.002230	1.110223e-16	1.221245e-15	[]	TOTAL	62	62	0.003907
4	R-HSA-9665686	9665686	Signaling by ERBB2 TMD/JMD mutants	True	True	48887	9606	Homo sapiens	TOTAL	30	10	0.001858	1.110223e-16	1.221245e-15	[]	TOTAL	13	13	0.000819

path = get_reactome(pi3ks,p_type='p')
path.head()

Running pathway analysis
Done

	name	reactome_id	p	-log10_p
0	GRB2 events in ERBB2 signaling	R-HSA-1963640	1.110223e-16	15.955
1	Signaling by ERBB2 ECD mutants	R-HSA-9665348	1.110223e-16	15.955
2	Signaling by ERBB2 KD Mutants	R-HSA-9664565	1.110223e-16	15.955
3	Signaling by ERBB2 in Cancer	R-HSA-1227990	1.110223e-16	15.955
4	Signaling by ERBB2 TMD/JMD mutants	R-HSA-9665686	1.110223e-16	15.955

path = get_reactome(pi3ks,p_type='FDR')
path.head()

Running pathway analysis
Done

	name	reactome_id	FDR	-log10_FDR
0	GRB2 events in ERBB2 signaling	R-HSA-1963640	1.221245e-15	14.913
1	Signaling by ERBB2 ECD mutants	R-HSA-9665348	1.221245e-15	14.913
2	Signaling by ERBB2 KD Mutants	R-HSA-9664565	1.221245e-15	14.913
3	Signaling by ERBB2 in Cancer	R-HSA-1227990	1.221245e-15	14.913
4	Signaling by ERBB2 TMD/JMD mutants	R-HSA-9665686	1.221245e-15	14.913

path[path.FDR<0.05]

	name	reactome_id	FDR	-log10_FDR
0	GRB2 events in ERBB2 signaling	R-HSA-1963640	1.221245e-15	14.913
1	Signaling by ERBB2 ECD mutants	R-HSA-9665348	1.221245e-15	14.913
2	Signaling by ERBB2 KD Mutants	R-HSA-9664565	1.221245e-15	14.913
3	Signaling by ERBB2 in Cancer	R-HSA-1227990	1.221245e-15	14.913
4	Signaling by ERBB2 TMD/JMD mutants	R-HSA-9665686	1.221245e-15	14.913
...	...	...	...	...
324	Signaling by Rho GTPases	R-HSA-194315	4.264432e-02	1.370
325	RUNX3 regulates p14-ARF	R-HSA-8951936	4.269110e-02	1.370
326	Cellular response to chemical stress	R-HSA-9711123	4.373732e-02	1.359
327	Signaling by Rho GTPases, Miro GTPases and RHO...	R-HSA-9716542	4.619382e-02	1.335
328	Metabolism of lipids	R-HSA-556833	4.924793e-02	1.308

329 rows × 4 columns

Reference

Download from Reactome/Download_data: https://reactome.org/download-data

Download UniProt to All pathways under Identifier mapping files

for type, there are IEA (Inferred from Electronic Annotation) and TAS (Traceable Author Statement, higher confidence)

ref = Data.get_reactome_pathway()

ref.head()

	uniprot	reactome_id	pathway	type	species
0	A0A023GPK8	R-DME-1500931	Cell-Cell communication	IEA	Drosophila melanogaster
1	A0A023GPK8	R-DME-373753	Nephrin family interactions	IEA	Drosophila melanogaster
2	A0A023GRW3	R-DME-72163	mRNA Splicing - Major Pathway	IEA	Drosophila melanogaster
3	A0A023GRW3	R-DME-72172	mRNA Splicing	IEA	Drosophila melanogaster
4	A0A023GRW3	R-DME-72203	Processing of Capped Intron-Containing Pre-mRNA	IEA	Drosophila melanogaster

uniprot='P31751' # AKT2
akt_path = query_reactome(uniprot) # AKT2

akt_path

	reactome_id	uniprot	pathway	type	species	lowest
0	R-HSA-109581	P31751	Apoptosis	IEA	Homo sapiens	0
1	R-HSA-109606	P31751	Intrinsic Pathway for Apoptosis	IEA	Homo sapiens	0
2	R-HSA-109703	P31751	PKB-mediated events	IEA	Homo sapiens	0
3	R-HSA-109704	P31751	PI3K Cascade	IEA, TAS	Homo sapiens	0
4	R-HSA-111447	P31751	Activation of BAD and translocation to mitocho...	IEA	Homo sapiens	1
...	...	...	...	...	...	...
93	R-HSA-9755511	P31751	KEAP1-NFE2L2 pathway	TAS	Homo sapiens	1
94	R-HSA-9755779	P31751	SARS-CoV-2 targets host intracellular signalli...	TAS	Homo sapiens	1
95	R-HSA-9824446	P31751	Viral Infection Pathways	TAS	Homo sapiens	0
96	R-HSA-9824585	P31751	Regulation of MITF-M-dependent genes involved ...	IEA	Homo sapiens	1
97	R-HSA-9856651	P31751	MITF-M-dependent gene expression	IEA	Homo sapiens	0

98 rows × 6 columns

# lowest
akt_path[akt_path.lowest==1].shape

(32, 6)

out = add_reactome_ref(path,uniprot)
out.shape

(406, 6)

Bar plot of pathways

plot_path(out)
plt.title('PI3K Pathways');

# All level
plot_path(out,p_type='FDR',ref_id_list=akt_path.reactome_id,top_n=15)
plt.title('PI3K Pathways (with highlight as overlap with all level Reactome database)');

out.head()

	name	reactome_id	FDR	-log10_FDR
0	GRB2 events in ERBB2 signaling	R-HSA-1963640	1.221245e-15	14.913
1	Signaling by ERBB2 ECD mutants	R-HSA-9665348	1.221245e-15	14.913
2	Signaling by ERBB2 KD Mutants	R-HSA-9664565	1.221245e-15	14.913
3	Signaling by ERBB2 in Cancer	R-HSA-1227990	1.221245e-15	14.913
4	Signaling by ERBB2 TMD/JMD mutants	R-HSA-9665686	1.221245e-15	14.913

# All level, use ref_col
plot_path(out,p_type='FDR',ref_col='ref_path',top_n=15)
plt.title('PI3K Pathways (with highlight as overlap with all level Reactome database)');

# All level
plot_path(out,p_type='FDR',ref_col='ref_path_lowest',top_n=15)
plt.title('PI3K Pathways (with highlight as overlap with lowest level Reactome database)');

Overlap

get_overlap(out, ref_id_list=akt_path.reactome_id,plot=True)

0.9081632653061225

get_overlap(out, ref_col='ref_path')

0.9081632653061225

get_overlap(out, ref_col='ref_path_lowest')

0.96875

Pipeline

out = get_reactome(pi3ks,p_type='FDR')
out = add_reactome_ref(out,'P31749') # kinase uniprot
accuracy = get_overlap(out, ref_col='ref_path',plot=True) # if lowest, change all to lo