Collection of scripts and notebooks to create panels in publication. This repository contains grid search preparation, execution and evaluation code used in the original ncem publication.
Next to python and shell scripts for grid searches and jupyter notebooks for results evaluation, this repository contains shallow infrastructure for defining hyperparameters in grid searches under ncem_benchmarks/. Install this package via pip install -e . into a python environment with an existing ncem installation to make this infrastructure available to the grid search scripts defined in this repository.
Before running grid searches, prepare the data as described in notebooks/data_preparation/. Grid searches and production model training can be run using the scripts as described in scripts/grid_searches/.
The MERFISH – brain, MIBI TOF – cancer, MELC – tonsils and CODEX – cancer datasets using in NCEM examples are publicly available. The chip cytometry – colon dataset has been generated by the Busch lab and is currently under review.
Zhang, M. et al. Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics. doi: 10.1101/2020.06.04.105700.
Hartmann, F. J. et al. Single-cell metabolic profiling of human cytotoxic T cells. Nat. Biotechnol. 39, 186–197 (2021).
Data can be downloaded from zenodo https://zenodo.org/record/3951613#.YQldJJMzadY To run NCEM download the scMEP_MIBI_singlecell.zip file and scMEP_sample_description.xlsx and store it to a data directory of your choice.
Pascual-Reguant, A. et al. Multiplexed histology analyses for the phenotypic and spatial characterization of human innate lymphoid cells. Nat. Commun. 12, 1737 (2021).
Data can be downloaded from zenodo https://zenodo.org/record/3744273#.YQlfkJMzYUE To run NCEM download the TONSILS_MFI_membranes_data_table.xlsx and the TONSILS_MFI_nuclei_data_table.xlsx and store it to a data directory of your choice.
Schürch, C. M. et al. Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front. Cell 183, 838 (2020).
Data can be downloaded from https://data.mendeley.com/datasets/mpjzbtfgfr/1 To run NCEM download the CRC_clusters_neighborhoods_markers.csv and store it to a data directory of your choice.