GO-term analysis
TF-COMB contains functionality for performing GO-term analysis on gene lists as obtained e.g. from TFBS annotation.
Obtain a list of genes from previous analysis
We will use a gene list containing genes upregulated in response to hypoxia (source msigdb: https://www.gsea-msigdb.org/gsea/msigdb/cards/HALLMARK_HYPOXIA.html)
[1]:
with open("../data/gene_list.txt") as f:
genes = f.read().split("\n")
[2]:
genes[:10]
[2]:
['ACKR3',
'ADM',
'ADORA2B',
'AK4',
'AKAP12',
'ALDOA',
'ALDOB',
'ALDOC',
'AMPD3',
'ANGPTL4']
Given a list of genes, you can use the GOAnalysis class to perform a GO-term analysis of the genes:
[3]:
from tfcomb.annotation import GOAnalysis
go_table = GOAnalysis().enrichment(genes)
INFO: Running GO-term enrichment for organism 'hsapiens' (taxid: 9606)
go-basic.obo: fmt(1.2) rel(2022-05-16) 47,071 GO Terms
HMS:0:00:05.707700 349,061 annotations, 20,717 genes, 18,963 GOs, 1 taxids READ: gene2go
INFO: Setting up gene ids
INFO: Setting up GO enrichment
Load BP Gene Ontology Analysis ...
Propagating term counts up: is_a
Load CC Gene Ontology Analysis ...
Propagating term counts up: is_a
Load MF Gene Ontology Analysis ...
Propagating term counts up: is_a
The results are seen in the returned table:
[4]:
go_table.head()
[4]:
| GO | name | NS | depth | enrichment | ratio_in_study | ratio_in_pop | p_uncorrected | p_fdr_bh | study_count | study_items | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 36 | GO:0005996 | monosaccharide metabolic process | BP | 4 | increased | 35/200 | 174/19351 | 2.699871e-07 | 0.000111 | 35 | ALDOA, ALDOB, ALDOC, ATF3, BRS3, ENO1, ENO2, E... |
| 31 | GO:0006091 | generation of precursor metabolites and energy | BP | 3 | increased | 32/200 | 365/19351 | 2.661620e-07 | 0.000111 | 32 | ALDOA, ALDOB, ALDOC, ENO1, ENO2, ENO3, GAA, GA... |
| 37 | GO:0006006 | glucose metabolic process | BP | 6 | increased | 29/200 | 113/19351 | 2.737493e-07 | 0.000111 | 29 | ALDOC, ATF3, BRS3, ENO1, ENO2, ENO3, FBP1, GAA... |
| 11 | GO:0016052 | carbohydrate catabolic process | BP | 4 | increased | 26/200 | 105/19351 | 1.366245e-07 | 0.000111 | 26 | ALDOA, ALDOB, ALDOC, ENO1, ENO2, ENO3, GAA, GA... |
| 21 | GO:0009141 | nucleoside triphosphate metabolic process | BP | 7 | increased | 23/200 | 203/19351 | 2.011868e-07 | 0.000111 | 23 | AK4, ALDOA, ALDOB, ALDOC, ENO1, ENO2, ENO3, GA... |
Plotting the enriched terms
The returned go_table is a subclass of pandas.DataFrame, which contains options for plotting the GO-enrichment results as seen here:
[5]:
type(go_table)
[5]:
tfcomb.annotation.GOAnalysis
[6]:
_ = go_table.plot_bubble()
The default aspect shown is “BP” (Biological Process), but by setting aspect, either of “CC” (Cellular Component) and “MF” (Molecular Function can be shown:
[7]:
_ = go_table.plot_bubble(aspect="CC")
[8]:
_ = go_table.plot_bubble(aspect="MF", n_terms=30)
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