GEOparse

Common errors

• AttributeError: 'tuple' object has no attribute 'name'

  cause This error occurs when code written for GEOparse 1.x (which returned a tuple from `get_GEO`) is run with GEOparse 2.x, which returns a single object. You're trying to access an attribute like 'name' directly on what is now the full `GESeries` object, but your code expects a tuple structure.
  fix Update your code to match the 2.x API. Instead of `gse, gsms = GEOparse.get_GEO(...)` and then `gse.name`, simply use `gse = GEOparse.get_GEO(...)` and then `gse.name`. Access individual samples via `gse.gsms`.

• requests.exceptions.ConnectionError: ('Connection aborted.', ConnectionResetError(104, 'Connection reset by peer'))

  cause The connection to the NCBI GEO server was abruptly closed during download, often due to network instability, a firewall blocking the connection, or the server closing the connection.
  fix Check your internet connection and proxy settings. Temporarily disable any firewalls or VPNs that might interfere. Try running the download again. If the issue persists, the GEO server might be experiencing temporary problems; try again later.

• KeyError: 'some_metadata_field_name'

  cause You are trying to access a specific metadata field (e.g., `gsm.metadata['some_field']`) that does not exist for the current GEO Series or Sample.
  fix Not all metadata fields are present for every entry. Use the `.get()` method for dictionary access with a default value to prevent `KeyError`: `gsm.metadata.get('some_metadata_field_name', 'N/A')`.

Warnings

• breaking The return type of `GEOparse.get_GEO()` changed significantly from versions 1.x to 2.x. Previously, it might have returned a tuple (e.g., `(gse_object, gsm_list)`). In 2.x, it consistently returns a single GEOparse object (e.g., `GESeries`, `GDS`, or `GSM`).
  Fix: Adjust your code to expect a single object from `get_GEO`. Access associated GSMs via the returned object's `.gsms` attribute (e.g., `gse.gsms`).
• gotcha Processing very large GEO datasets can consume significant amounts of RAM and disk space, potentially leading to out-of-memory errors or long download/parsing times.
  Fix: Consider downloading files to disk using `destdir`, processing data in chunks if possible, or filtering data early. Ensure sufficient disk space and memory before attempting to parse extremely large datasets.
• gotcha Downloads from the GEO database can occasionally fail due to network connectivity issues, server-side problems at NCBI, or incorrect GEO accession IDs.
  Fix: Implement robust error handling (e.g., `try-except` blocks for `requests.exceptions.ConnectionError`), check your internet connection, verify the GEO accession ID on the NCBI GEO website, and consider implementing retry logic for downloads.

Install

• pip install geoparse Install stable version

Imports

• GEOparse

  import GEOparse

• get_GEO

  from GEOparse import get_GEO

  Can also be accessed via `GEOparse.get_GEO` after `import GEOparse`.

Quickstart

This quickstart demonstrates how to download and parse a GEO Series (GSE) entry, access its metadata, and iterate through its associated GEO Samples (GSMs) to view their data tables. It uses 'GSE1' for a minimal example.

import GEOparse
import os

# Download a small GEO Series (GSE1 is very small for quick testing)
print("Downloading GSE1 data...")
gse = GEOparse.get_GEO(geo="GSE1", destdir="./")

print(f"\nSuccessfully parsed GEO Series: {gse.name}")
print(f"Title: {gse.metadata.get('title', ['N/A'])[0]}")
print(f"Number of samples (GSMs): {len(gse.gsms)}")

# Access and print information for the first sample
if gse.gsms:
    first_gsm_name = list(gse.gsms.keys())[0]
    first_gsm = gse.gsms[first_gsm_name]
    print(f"\nFirst Sample (GSM): {first_gsm.name}")
    print(f"Sample Title: {first_gsm.metadata.get('title', ['N/A'])[0]}")
    print(f"Sample Type: {first_gsm.metadata.get('type', ['N/A'])[0]}")
    print(f"Sample Table Head:\n{first_gsm.table.head(2)}")