bramalingam / idr-notebooks

Jupyter Notebooks for the Image Data Resource

idr-notebooks

A set of Python Notebooks to demonstrate how to access the images and metadata from the Image Data Repository (IDR, https://idr.openmicroscopy.org), including features and all descriptive tags.

Full access to IDR metadata and images is provided through the standard OMERO API, documentation for which can be found here, with the Python bindings found specifically here. The notebooks in this repository are meant to exemplify the use of that API in the context of the IDR, and the sort of queries that can be done. In particular, they show how to reproduce Figure 1 and Figure 2 of the paper.¹ They also make use of the scipy ecosystem, including pandas.

Notebook	Lang	Level	Description	Launch2
Using Jupyter	Markdown	Intro	Getting a login account	-
IDR API example script	Py	Intro	Shows an example of using the web API to extract metadata from the IDR. Can also be launched locally.	launch
Getting Started	Py	Intro	How to connect, some simple data access	launch
Figure 1 Sample of Phenotypes	Py	Paper	Reproduces Fig. 1 of the paper: downloads annotations from all screens and computes and plots some statistics	launch
Gene Network	Py	Paper	Reproduces Fig. 2 of the paper: downloads annotations from 3 screens,with a phenotype in common, queries StringDB for interactions and plots the resulting network.,Uses a conversion table for orthologues and gene identifiers which was built offline using biomart,(see article for more details.). It uses bokeh and py2cytoscape to display networks.	launch
Rohn Phenotype Clustering	Py	Study details	Downloads annotations from IDR008, and performs some simple phenotypic clustering, building a figure,similar to Fig. 1 of the corresponding paper. Builds a gallery of thumbnails from images of several phenotypes.	launch
PCA analysis of Charm features	Py	Study details	Shows how to access the computed CHARM features using OMERO.tables,and performs some analysis on them, showing that single cell information can be accessed from generic tile-based features,without segmentation.	launch

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1: Available on bioRxiv under https://doi.org/10.1101/089359

2: If you don't yet have an account, notebooks can be viewed under http://github.com/IDR/idr-metadata or more completely under https://nbviewer.jupyter.org/github/idr/idr-notebooks/tree/master/