CLUSTER3(1)

📦 version 1.59, in debian bookworm, ubuntu jammy, ubuntu noble

💖 CLUSTER3(1) — the manual, but make it cute 💖

okay bestie, so this is the cluster3 page from the General Commands Manual, section 1. yes she's a real one. let's get into it 🧚

✨ NAME ✨

cluster3 — Eisen-clustering of microarray data. that's the whole vibe. you feed her microarray data, she clusters it. iconic behavior fr fr 🌸

🌈 SYNOPSIS 🌈

cluster3 [-f filename]  [-l 0|1]  [-u jobname]  [-g [0..9]]  [-e [0..9]]
[-m [msca]]  [-k number]  [-s 0|1]  [-x number]  [-y number]

🎀 OPTIONS 🎀

every single one, no skipping, we don't do that here 💅

  • -h--help — shows you a lil summary of all the options. when in doubt, ask for help. main character move honestly.
  • -f filename — file loding. that's where your file goes, bestie 📂
  • -u jobname — lets you pick a different name for your output files. the default is derived from the input file name, so if you don't set this she just names things after your input. rude but fair ✨
  • -l 0|1 — do you want to log-transform the data or not. default is 0, aka no log-transform. leave it alone and she takes the data as-is 🦋
  • -k number — whether to run k-means clustering instead of hierarchical clustering, plus the number of clusters k you want. default: 0 👑
  • -x number — the horizontal dimension of the SOM grid. default: 2 ⭐
  • -y number — the vertical dimension of the SOM grid. default: 1 ⭐
  • -s 0|1 — whether to calculate an SOM instead of hierarchical clustering. default: 0 🌸
  • -v, --version — shows the version of the program. slay, know your build 💜
  • -g [0..9] — the distance measure for gene clustering. options are:
    • 0: No gene clustering
    • 1: Uncentered correlation
    • 2: Pearson correlation
    • 3: Uncentered correlation, absolute value
    • 4: Pearson correlation, absolute value
    • 5: Spearman's rank correlation
    • 6: Kendall's tau
    • 7: Euclidean distance
    • 8: Harmonically summed Euclidean distance
    • 9: City-block distance default: 1 🍓
  • -e [0..9] — the distance measure for microarray clustering. the lineup:
    • 0: No clustering
    • 1: Uncentered correlation
    • 2: Pearson correlation
    • 3: Uncentered correlation, absolute value
    • 4: Pearson correlation, absolute value
    • 5: Spearman's rank correlation
    • 6: Kendall's tau
    • 7: Euclidean distance
    • 8: Harmonically summed Euclidean distance
    • 9: City-block distance default: 0 🍓
  • -m [msca] — which hierarchical clustering method to use. pick your fighter:
    • m: Pairwise complete-linkage
    • s: Pairwise single-linkage
    • c: Pairwise centroid-linkage
    • a: Pairwise average-linkage default: m 🔥

👀 SEE ALSO 👀

mapletree (1), smile (1). go read those too, they're giving collab energy 🫶

💌 AUTHOR 💌

This manual page was written by Steffen Moeller moeller@pzr.uni-rostock.de for the Debian system (but may be used by others).

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU General Public License, Version 2 any later version published by the Free Software Foundation.

On Debian systems, the complete text of the GNU General Public License can be found in /usr/share/common-licenses/GPL.

okay that's the whole thing, bestie!! 🎀 and for the sign-off: this was the cluster3(1) page from the General Commands Manual — no cap, that's literally the whole footer, just the page name. go cluster something iconic 💖✨🦋

📦 where this page comes from