[an error occurred while processing this directive]

Murphy Lab

Home
Information
People
Addresses
Cytometry Development Workshop
FCS API

Research
Projects
Publications
Software
Presentations
Flow Cytometry

Affiliations
Carnegie Mellon University
Computational Biology Department
Center for Bioimage Informatics
Biological Sciences Department
Biomedical Engineering Department
Machine Learning Department
MBIC

[an error occurred while processing this directive]

Internal

Information
Lab FAQ
Lab Research Topics

Services
TypIX

Web Pages
Web Page Template
Visitation Statistics
Important Links

Software and Documentation
Matlab Docs
Khoros Docs
TN-Image Docs
Michael Boland's thesis

Murphy Lab - Software - eLife 2016 - Active Learning Of Perturbations

The software, primary data and intermediate results used for the following paper can be downloaded below:

A. W. Naik, J. D. Kangas, D. P. Sullivan, and R. F. Murphy (2016) Active Machine Learning-driven Experimentation to Determine Compound Effects on Protein Patterns. eLife, in press (DOI).

Licenses

This source code is released under GNU LGPL v2.1.

Images and other materials are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Downloads

The data and code are contained in the following files.

Source Code

eLife_AL_source_code.tar [1.6 MB]
eLife_AL_clustering_code.tgz [12 KB]

Input Data

Intermediate Results

These files can be used to regenerate the tables and figures in the paper.

eLife_AL_intermediate_data.tar [2.4 GB]

Recreating results

To recreate the results from the article (i.e. the figures and tables) from the primary data or intermediate results,

Download and expand the source code to the desired directory.
wget -nc http://murphylab.web.cmu.edu/software/2016_eLife_Active_Learning_Of_Perturbations/eLife_AL_source_code.tgz
tar -xzf eLife_AL_source_code.tgz
Either download and expand the images, additional images and primary data into the same root directory (note that the images tar file is 666 GB),
wget -nc http://murphylab.web.cmu.edu/software/2016_eLife_Active_Learning_Of_Perturbations/eLife_AL_images.tar
tar -xf eLife_AL_images.tar
wget -nc http://murphylab.web.cmu.edu/software/2016_eLife_Active_Learning_Of_Perturbations/eLife_AL_additional_images.tar
tar -xf eLife_AL_additional_images.tar
wget -nc http://murphylab.web.cmu.edu/software/2016_eLife_Active_Learning_Of_Perturbations/eLife_AL_primary_data.tar
tar -xf eLife_AL_primary_data.tar
Or download and expand the intermediate results into the same root directory.
wget -nc http://murphylab.web.cmu.edu/software/2016_eLife_Active_Learning_Of_Perturbations/eLife_AL_intermediate_data.tar
tar -xf eLife_AL_intermediate_data.tar
Go into the code directory and run the code
source RUNME.sh

Note that the script will check whether the intermediate results files are present and skip creating them from the primary data if they are.

System requirements

Python 2.7.9 with packages:
- numpy 1.9.2
- mahotas 1.3.0
- scipy 0.15.1
- sklearn 0.16.0
- pylab 1.4.3
- networkx 1.10

This software has been tested using Python 2.7.9 under CentOS 6.5 and Ubuntu 13.10.

Last Updated: 19 Dec 2016