Logical Clustering Suite v1.1 (Win PCs)

[niethamp]

### Simple Gene Correlation Analysis (sGCA) by Permutated Logical Clustering

This is the standalone version of the Logical Clustering Suite (v1.1) for Win PCs. Its installation requires download of MATLAB runtime as wrapper.

• 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.
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This discussion was created from the release Logical Clustering Suite v1.1 (Win PCs).