This directory contains scripts used to process and analyze screens from the ALS patient-derived fibroblast study. We provide a Dockerfile to install all dependencies for running analyses reported in Kumbier et al. 2024.
docker build -t als/als .
docker run -it --rm -v <path to project_als directory>:/ALS als/als
The core analysis scripts used for each screen / analysis include:
-
preprocessing
: directory containing scripts for processing raw image-derived features into the selected set of ALS-relevant eigenfeatures. Proecsses image features are available in thedata_profiles
directory of the zenodo repository. Raw image features and images are available upon request. -
utilities.R
: script containg functions for fitting models along with helper functions for data processing and visualization. -
color_palette.R
: sets color palette used in figures.
Scripts used to generate figures for the paper have been copied to
paper_figures
and are for the most part organized by figure.
-
Figure_Search
: analyses of imaging marker set search—reported in supplemental section. -
Figure_Scores
: analyses for image-based scores (i-MAP scores). -
Figure_Transcriptomics
: analyses for transcriptomic-based scores (t-MAP scores). -
Figure_ASO
: analyses from ASO screen. Note: some of the sporadic figures are generated inFigure_Transcriptomics
Data are available through the Zenodo repository:
https://zenodo.org/records/10499037. Data for image-based cell profiles are
contained in data_profiles
, organized by screen. All other data can be found
in data
.