cytomapper:
Highly multiplexed imaging cytometry acquires single-cell expression values of selected proteins in a spatially-resolved fashion. These measurements can be visualized across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualized on segmented cell areas. This package contains functions for the visualization of multiplexed read-outs and cell-level information obtained by multiplexed imaging cytometry. The main functions of this package allow 1. the visualization of pixel-level information across multiple channels and 2. the display of cell-level information (expression and/or metadata) on segmentation masks.
For the official release version, please visit: https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html
The development version can be installed from Github: https://github.com/BodenmillerGroup/cytomapper
histoCAT:
histoCAT is a platform for Imaging Mass Cytometry multidimensional image analysis
Downloads for histoCAT Here
Check out The Manuscript (Schapiro et al. 2017, Nature Methods). Here
Downloads for histoCAT++ Here
Check out The Manuscript (Catena et al. 2018, Journal of Pathology). Here
AirLab:
AirLab is a cloud-based laboratory-management tool tailored for antibody-based research.
Manage easily
- Antibody stocks
- Panels for CyTOF and Helios
- Results and experiments
AirLab is available at www.airlaboratory.ch
You can also download the iPhone/iPad app and connect to AirLab from the iTunes App Store and carry your laboratory in your pocket.
The code for this project is available at GitHub
Check out AirLab’s publication in Genome Biology.
Catena et al. 2016, Genome biology
Adnet:
Adnet is a set of analysis scripts used for the paper: “Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry” Xiao-Kang Lun, Vito RT Zanotelli, James D Wade, Denis Schapiro, Marco Tognetti, Nadine Dobberstein & Bernd Bodenmiller
The repository is available in Github
Check out The Manuscript here. Lun et al. 2017, Nature Biotechnology biology