CNVKIT_SCATTER(1)

💅 CNVKIT_SCATTER(1) — plot probe log2 coverages AND segmentation calls together, periodt

okay so bestie, welcome to cnvkit_scatter(1), aka the part of the CNVkit universe where we make pretty pictures of your copy ratios. It's a User Command, it's iconic, it's giving "I visualize your genome and I do it flawlessly". Let's go. 🦋

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✨ NAME ✨

cnvkit_scatter — Plot probe log2 coverages and segmentation calls together. no cap, that's literally the whole job. 🎀

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🌸 DESCRIPTION 🌸

Here's the vibe — this is how you call it:

usage: cnvkit.py scatter [-h] [-s FILENAME] [-c RANGE] [-g GENE]
       [-l RANGE_LIST] [-w WIDTH] [-o FILENAME]
       [-a CHARACTER] [--by-bin] [--segment-color SEGMENT_COLOR]
       [--title TITLE] [-t] [--y-max Y_MAX] [--y-min Y_MIN] [--fig-size
       WIDTH HEIGHT] [-v FILENAME] [-i SAMPLE_ID] [-n NORMAL_ID] [-m
       MIN_VARIANT_DEPTH] [-z [ALT_FREQ]] [filename]

(Yeah the usage line is long. It's a lot of options. She contains multitudes. 💅)

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🧚 POSITIONAL ARGUMENTS 🧚

• filename — your processed bin-level copy ratios, i.e. the *.cnr file. That's the output of the fix sub-command, bestie. If you don't have one of those, you're not even at the party yet. 🍓

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👑 OPTIONS 👑

• -h, --help — shows this help message and then dips. bye! ✨
• -s FILENAME, --segment FILENAME — your segmentation calls (.cns), which is the output of the segment command. Feed the scatter the segments, she'll draw them for you.
• -c RANGE, --chromosome RANGE — pick a chromosome or a chromosomal range to display, like 'chr1' or 'chr1:2333000-2444000'. And listen: if you give a range, all the targeted genes inside that range get shown, unless you also pass -g/--gene. iykyk.
• -g GENE, --gene GENE — the name of the gene (or genes, comma-separated) you wanna display. one gene or a whole girl group, your call. 🫶
• -l RANGE_LIST, --range-list RANGE_LIST — a file listing all the chromosomal ranges to display, given as BED, interval list, or 'chr:start-end' text. This makes focal plots, kinda like -c/--chromosome, for every listed region, and combines them all into one multi-page PDF. ⚠️ Heads up: you must also specify the output filename with -o/--output, or it's not happening.
• -w WIDTH, --width WIDTH — how much margin to show around the selected gene(s) (-g/--gene) or the small chromosomal region (-c/--chromosome). Default is 1000000. that's a lot of zeros and she earned every one of them. 💀
• -o FILENAME, --output FILENAME — the output PDF file name. yeah. name your PDF. do it.

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🎨 Plot Aesthetics 🎨

• -a CHARACTER, --antitarget-marker CHARACTER — use this symbol to plot antitargets when you're plotting inside a selected chromosomal region (-g/--gene or -c/--chromosome). Default is the same as targets. matchy matchy, cute.
• --by-bin — plots the data's x-coordinates by bin indices instead of genomic coordinates. So: every bin gets equal width, no blank regions show up, and the x-axis values mean bin number (within the chromosome) instead of genomic position. it's giving "organized". ✨
• --segment-color SEGMENT_COLOR — plot those segment lines in this color. It can be any string matplotlib accepts, like 'red' or '#CC0000'. go off, pick a slay hue. 💖
• --title TITLE — the plot title. Default is the sample ID, taken from the filename or from -i.
• -t, --trend — draws a smoothed local trendline on the scatter plot. aesthetic AND informative, we love a multitasker. 🔥
• --y-max Y_MAX — the y-axis upper limit.
• --y-min Y_MIN — the y-axis lower limit.
• --fig-size WIDTH HEIGHT — the width and height of the plot, in inches. Default is predefined in the Matplotlib 'rcParams' variable (most of the time that's '6.4 4.8'). resize your girl, she won't mind. 🌈

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🧬 To Plot SNP B-Allele Frequencies 🧬

• -v FILENAME, --vcf FILENAME — the VCF file name containing the variants you want to plot for SNV b-allele frequencies.
• -i SAMPLE_ID, --sample-id SAMPLE_ID — the name of the sample in the VCF to use for b-allele frequency extraction, and also as the default plot title. she's the main character AND the label. 👑
• -n NORMAL_ID, --normal-id NORMAL_ID — the corresponding normal sample ID in the input VCF. This sample gets used to select only germline SNVs to plot. germline only, bestie, we're filtering.
• -m MIN_VARIANT_DEPTH, --min-variant-depth MIN_VARIANT_DEPTH — the minimum read depth for a SNV to be used in the b-allele frequency calculation. Default is 20. shallow reads need not apply. 🙈
• -z [ALT_FREQ], --zygosity-freq [ALT_FREQ] — ignore the VCF's genotypes (the GT field) and instead infer zygosity from allele frequencies. If you use it without a number, the default is 0.25. trust the math, not the field. 😭

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and that's the whole page, bestie!! 💜 this manual page came to you from cnvkit.py scatter version 0.9.10, dated July 2023 — go make some gorgeous plots, you absolute legend. 🎀✨🦋