CORRECT_ABUNDANCES(1)

✨ CORRECT_ABUNDANCES ✨

okay bestie, welcome to correct_abundances — it lives in section 1, the User Commands corner of the manual, and it's literally the glow-up step where your genome abundances get their similarity correction. 💅

🌸 NAME 🌸

correct_abundances — run the genome abundance similarity correction step

🦋 SYNOPSIS 🦋

correct_abundances NAMES

💖 DESCRIPTION 💖

Run the similarity correction step. That's the whole vibe. ✨

Note: so like, yes, technically you can run the read mappers by hand, or hand-craft the similarity matrix yourself if that's your main character moment. But we strongly recommend you use the provided Python scripts run_mappers.py and create_similarity_matrix.py instead. fr fr. trust. 🫶

🎀 OPTIONS 🎀

• NAMES — the filename of the names file. It's a plain text file and it should have one name per line, bestie. That name gets used as the identifier all the way through the whole algorithm, so pick good ones. 👑
• -h, --help — shows this help message and then exits. iconic behaviour honestly.
• -m SMAT, --similarity-matrix=SMAT — path to the similarity matrix file. important: the similarity matrix must be created with the same NAMES file, no mixing and matching. [default: ./similarity_matrix.npy]
• -s SAM, --samfiles=SAM — a pattern pointing to the SAM files that the mapper created. The placeholder for the name is "%s". so it slots your name right in there. [default: ./SAM/%s.sam]
• -b BOOT, --bootstrap-samples=BOOT — sets the number of bootstrap samples. use 1 to disable bootstrapping entirely. [default: 100]
• -o OUT, --output=OUT — the plain text output file where the results land. [default: ./results.txt]

and that's the whole page, no notes, you're gonna slay this correction step 💖

this lil legend is correct_abundances SVNr18, dated February 2014 — so yeah she's been serving since 2014 and she's still here. periodt. 🌈⭐