marburg_biobank

Introduction

The marburg_biobank python module offers a high level interface to the data sets stored in the [Ovarian Cancer Effusion Biobank and Database])(https://www.ovara.net/biobank).

The basic usage is as follows:

import marburg_biobank
db = marburg_biobank.OvcaBiobank("marburg_ovca_revision_15.zip") #  you need to download that file from your biobank.
print(db.list_datasets())
df_wide = db.get_wide('transcriptomics/rnaseq')  # to retrieve the data in a one sample per column / one row per measured variable format
df_tall = db.get_dataset('transcriptomics/rnaseq') # to retrieve the data in one row per data point format

Data formats available

wide

Using db.get_wide(dataset):

A pandas DataFrame that looks like this

Caveats: If a dataset has only one compartment, the compartment information is ommited by get_wide(), unless .get_wide(standardized=True) is used. The same applies for the unit in the index. If there is a 'name' column in dataset, it get's added to the index, regardless of the value of standardized.

tall

Using: db.get_dataset(dataset)):

A pandas DataFrame that looks like this

This is the internal storage format.

compartments

Compartments are an abstraction on top of 'cells' and 'bio-liquid'. Examples are Tumor associated macrophages (TAMs), Tumor cells (TU), ascites, blood... db.get_compartments() provides a list

Datasets

Datasets are organized three levels deep. The first one defines the whether you're looking t ex-vivo (=primary) data or in-vitro experiments (=secondary) or literature data (=tertiary). The second level defines *omics being measured (transcriptomics, proteomics, ... or 'clinical'), while the third levels defines the actual method (RNaseq, FACS,...)

Survival data is in primary/clinical/survival.

Please remember: if using https://pypi.python.org/pypi/lifelines, censored and event are negations of each other.

Excluded patients:

Exclusion can either be on a patient, or a patient+compartment level. In addition, there is per dataset exclusion and global exclusion.

Exclusion is by default applied to db.get_wide(), but not to db.get_dataset(), you can change the default by passing apply_exclusion=True|False.

Exclusion information can be retrieved by db.get_excluded_patients(dataset), which return a set of patients (or patient+compartment tuples), or db.get_exclusion_reasons(), which lists why the exclusion happend.