Gene ontology enrichment analysis using protein expression.
Project description
gopher
Gene ontology enrichment analysis using protein expression.
Gopher uses a Mann-Whitney U Test to look for enriched gene ontology terms that are present when proteins are ranked by a quantitative value, such as the difference between two conditions or the abundance of the protein.
Installation
Gopher can be pip installed directly from GitHub:
pip install git+https://github.com/TalusBio/gopher.git
Usage
Gopher can be used within Python.
Currently, Gopher is pretty slow---we recommend making use of the go_subset
argument to limit the number of GO terms considered by Gopher.
Here is an example:
# Import packages
import gopher
import matplotlib.pyplot as plt
import seaborn as sns
# Only test a few cellular compartment GO terms:
terms = [
"nucleus",
"nuclear chromosome",
"nucleoplasm",
"euchromatin",
"heterochromatin",
"protein-DNA complex",
"transcription regulator complex",
"inner mitochondrial membrane protein complex",
"mitochondrial nucleoid",
"cell surface",
"ER to Golgi transport vesicle membrane",
"organelle membrane",
"lysosome",
"cytoplasm",
]
# Read data from an EncyclopeDIA output:
proteins = gopher.read_encyclopedia("RESULTS-quant.elib.proteins.txt")
# Peform the GO enrichment analysis:
results = gopher.test_enrichment(
proteins=proteins,
aspect="cc",
go_subset=terms,
progress=True,
)
# Format for plotting:
long_df = results.melt(
["GO Accession", "GO Name", "GO Aspect"],
var_name="Run",
value_name="pvalue",
)
long_df["neglogpval"] = -np.log10(long_df["pvalue"])
# Create a plot:
plt.figure(figsize=(8, 3))
sns.barplot(data=long_df, x="GO Name", y="neglogpval", hue="Run")
plt.ylabel("$-\log_{10}$ p-value")
plt.xticks(rotation=90)
plt.tight_layout()
plt.show()
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