Some scripts to prepare ontology long table for enrichment and GSEA analysis.

Requirements

python3 -m pip install pandas owlready2 retrying openpyxl

Fetch ontologies from Oryzabase

Just run this, annotation will be downloaded from Oryzabase annotation.

python3 scripts/get_ontologies_from_oryzabase.py

Clean JGI Sitalica annotation info

First, download Sitalica_312_v2.2.annotation_info.txt from JGI Sitalica annotation

Then replace the jgi_si_annotation path in scripts/clean_jgi_si_annotation.py.

Finally, run this.

python3 scripts/clean_jgi_si_annotation.py

Clean GO annotation from TAIR

First download GO annotation from TAIR

aria2c "https://www.arabidopsis.org/api/download-files/download?filePath=GO_and_PO_Annotations/Gene_Ontology_Annotations/ATH_GO_GOSLIM.txt.gz"
gzip -d ATH_GO_GOSLIM.txt.gz

Then run the script.

python3 scripts/clean_ath_go.py

TAIR Gene Search Results

in TAIR Gene Search page, use different chromosome as filter, after clicking "Submit Query" bottom and search results displayed, click "Download All" bottom to download result tsv file.

Enrichment Analysis using clusterProfiler

install.packages("readxl")
install.packages("BiocManager")
BiocManager::install("clusterProfiler")

onto = readxl::read_excel("results/oryzabase-ontologies.xlsx", sheet="RAP_GO")

gene = c("Os01g0118100", "Os01g0549700", "Os02g0710800", "Os03g0108600", "Os03g0158200", "Os03g0746500")
universe = NULL

enrich_res = clusterProfiler::enricher(
    gene=gene,
    universe=universe,
    TERM2GENE=onto[c("OntoID", "GeneID")],
    TERM2NAME=onto[c("OntoID", "Description")]
)

write.csv(as.data.frame(enrich_res), "enrich_res.csv")

svg("demo_dotplot.svg")
clusterProfiler::dotplot(enrich_res)
dev.off()