Version 1.34 (25.4 MB) by Philipp
Logical clustering suite with graphical user interface.
Updated 5 Sep 2023

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This is the **standalone version of the Logical Clustering Suite (v1.34) for Mac PCs**. Its installation requires download of MATLAB runtime (free) 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.
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Cite As

Ma, Yanan, et al. “Oxoeicosanoid Signaling Mediates Early Antimicrobial Defense in Zebrafish.” Cell Reports, vol. 42, no. 1, Elsevier BV, Jan. 2023, p. 111974, doi:10.1016/j.celrep.2022.111974.

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MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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