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PyPI-Server Unit tests

expressionatlas

A Python client for searching and downloading gene expression datasets from EMBL-EBI Expression Atlas, providing full compatibility with the R Bioconductor package.

Note

This package is a fork of expression-atlas to use BiocPy data structures.

Install

To get started, install the package from PyPI

pip install expressionatlas

Get Started

Expression Atlas is a comprehensive resource of gene and protein expression data across species and biological conditions. This Python package provides programmatic access to:

  • Search: Query thousands of curated RNA-seq and microarray experiments
  • Download: Retrieve experiment data with automatic format handling
  • Analyze: Work with R-compatible data structures in Python

Basic Usage

from expression_atlas import ExpressionAtlasClient

# Initialize client
client = ExpressionAtlasClient()

# Search for experiments
results = client.search_experiments(
    properties=["cancer", "breast"],
    species="homo sapiens"
)
print(results.head())
#   Accession        Species                Type  ...
# 0 E-MTAB-1624  homo sapiens  microarray data  ...

Download RNA-seq Data

# Download a single experiment
exp = client.get_experiment("E-MTAB-7041")

# Access RNA-seq data (SummarizedExperiment)
rnaseq = exp["rnaseq"]
counts = rnaseq.assay("counts")  # numpy array: genes × samples

print(f"Shape: {counts.shape[0]} genes × {counts.shape[1]} samples")
# Shape: 58735 genes × 48 samples

# Sample metadata (BiocFrame)
sample_info = rnaseq.get_column_data()
print(sample_info.get_column_names())

# Gene annotations (BiocFrame)
gene_info = rnaseq.get_row_data()
print(gene_info.shape)

Download Microarray Data

exp = client.get_experiment("E-MTAB-1624")

# Microarray data is keyed by array design
array_design = "A-AFFY-126"
eset = exp[array_design] # This is also a SummarizedExperiment now

# Expression matrix (probes × samples)
intensities = eset.assay("exprs")
print(intensities.shape)
# (54675, 96)

# Sample metadata (BiocFrame)
sample_annotations = eset.get_column_data()
print(sample_annotations.shape)

# Feature annotations (BiocFrame)
probe_annotations = eset.get_row_data()

Batch Downloads

# Download multiple experiments
accessions = results["Accession"].head(10).tolist()
experiments = client.get_experiments(accessions)

# Access individual experiments
for acc, exp in experiments.items():
    if exp is not None:
        print(f"{acc}: {exp['rnaseq'].shape if 'rnaseq' in exp else 'microarray'}")

Note

This project has been set up using BiocSetup and PyScaffold.