MiST now automatically uses the scaled specificity score (specificity18, by default) in the combined MiST score. See docs/ScalingSpecificity.pdf for a discussion of this change. This means MiST thresholds and weights should be closer to those used in the original study, but also scores will be sensitive to MiST version. Don't change versions mid-study without changing your yml file!
You can disable the use of specificity score scaling in the combined MiST score by changing your config yml file to include:
standardize_specificity : FALSE
See tests/small/mist_small_test.yml for an example config yml file.
We do not recommend disabling this in general, but it can be useful for consistency with previous versions. Regardless of the setting, the output will include columns for both the scaled and unscaled specificity; this setting changes which specificity score will be used in MiST score.
Workstation running any current OS, Unix environment recommended
- R package (http://www.r-project.org)
- R packages: getopt, optparse, reshape2, pheatmap, RcolorBrewer, ggplot2, MESS, yaml
- MiST source code (https://github.com/everschueren/MiST)
- Git (optional) (http://git-scm.com)
- Download the MiST package as a .zip archive from the public GitHub repository by clicking on the “Download ZIP” button on the bottom right, unzip the files and
- move the directory to a permanent location.
- Alternatively, you can check out the MiST package through Git as follows:
- git clone https://github.com/everschueren/MiST.git MiST
- The MiST pipeline is designed to run from a terminal using R. This requires the user to have executable permissions. To set these permissions in a Unix environment, navigate in the terminal to the MiST directory, hereafter referred to as the $INSTALL_DIR, then type: sudo chmod -R 775 *
To test your installation, navigate to the ./tests/small directory within the MIST downloads and run MIST there. On MacOSX and other unix terminals, commands would look like this:
cd mist/tests/small
Rscript ../../main.R -c mist_small_test.yml
Output will appear within a subdirectory of your current working directory at processed/preprocessed_NoC_MAT_MIST.txt
- Jäger, S., Cimermancic, P., Gulbahce, N. et al. Global landscape of HIV–human protein complexes. Nature 481, 365–370 (2012). https://doi.org/10.1038/nature10719 (See Supplementary Information, page 46)
- Verschueren, E., Von Dollen, J., Cimermancic, P., Gulbahce, N., Sali, A., & Krogan, N. J. (2015). Scoring Large-Scale Affinity Purification Mass Spectrometry Datasets with MiST. Current protocols in bioinformatics, 49, 8.19.1–8.19.16. https://doi.org/10.1002/0471250953.bi0819s49. (May be freely available at PMC)