LCS_v1.39

Versione 1.39 (957 KB) da Philipp
Logical clustering suite with graphical user interface.
2 download
Aggiornato 20 apr 2024

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Permutated logical clustering of gene expression profiles. Please cite Ma et al., Cell Rep, 2023. This is an experimental application: interpret LCS results with caution.
This is the Matlab app of the Logical Clustering Suite (v1.38) for Mac and PCs. Its installation requires download of MATLAB runtime (free) as wrapper. The app has only been tested for PC, but should also work for Mac.
v1.38 update notes:
-Only accepts GCA data files >=v1.38 (sorry, data needs to be reformatted with this app)
-New feature: One-way ANOVA multicomparison test. ANOVA p-values are included for each gene in the clustered data table to allow thresholding & sorting. The calculation uses parallel processing. An interactive multicomparison graph allows to manually pick the control group for genes of interest (GOIs, added in the text box). The GOI ANOVA results can be saved in an Excel table.
-compiled standalone version and updated manual will follow later, and be posted to the GitHub project site.
-for v1.34 manual and accessory files, please see project website on GitHub.
v1.39 update notes:
-Small bug fix in the sGEA module.
General application notes:
-The Logical Clustering Suite (LCS) clusters gene expression profiles or similar data by permutated logical gating according to their “Ideal Phenotypes” (IPs), which are defined by all possible experimental outcomes.
- Logical clustering conceptually differs from K-means-, SOM, DBSCAN and alike clustering methods that cluster gene expression profiles just according to their mutual similarity without taking the experimental groups into account.
- When just comparing two experimental groups, logical clustering simplifies to something like DESeq2 with only two possible IPs, 0 1 for upregulation & 1 0 for downregulation. Thus, methods like DESeq2, may be conceptualized as a special instance of logical clustering.
- In summary, logical clustering assumes that the locations & number of **all experimentally meaningful cluster centers are given** by the experimental design. Gene expression profiles more similar to one IP than to all the other IPs, form a logical cluster.
- Logical clustering by simple (=logic) gene correlation analysis (sGCA) was introduced in Ma Y, Hui KL, Gelashvili Z, Niethammer P. Oxoeicosanoid signaling mediates early antimicrobial defense in zebrafish. Cell Rep. 2023 Jan 31;42(1):111974. doi: 10.1016/j.celrep.2022.111974. Epub 2023 Jan 10. PMID: 36640321; PMCID: PMC9973399. Please cite if you are using LCS.
To help improving this application, please send feedback to [sgcafeedback@gmail.com](mailto:sgcafeedback@gmail.com).
If you like LCS, please follow us on https://twitter.com/NiethammerLab

Cita come

Philipp (2024). LCS_v1.39 (https://www.mathworks.com/matlabcentral/fileexchange/164111-lcs_v1-39), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2024a
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Versione Pubblicato Note della release
1.39