usage: __main__.py [-h] --intensities INTENSITIES --array ARRAY --genome
                   GENOME --region REGION [--kmer-size KMER_SIZE]
                   [--best-pval] [--reverse] [--seed SEED]
                   [--max-probes MAX_PROBES] [--save-figure SAVE_FIGURE]
                   [--holm] [--rand-n RAND_N] [--diagnostics]

Refactored scan-mode motif regression

options:
  -h, --help            show this help message and exit
  --intensities INTENSITIES
                        Path to probe intensity file
  --array ARRAY         Path to k-mer array file mapping k-mers to genomic
                        regions
  --genome GENOME       Path to reference genome in FASTA format
  --region REGION       chr:start-end (1-based inclusive)
  --kmer-size KMER_SIZE
                        K-mer size (default: 8)
  --best-pval           Summarize non-pooled scan by minimum p-value; with
                        --holm, use SNV fits and same-window RAND support
                        instead
  --reverse             Use reverse complement of the sequence
  --seed SEED           Seed for max-probes subsampling (default: 0); RAND
                        background retains its existing deterministic
                        sampling.
  --max-probes MAX_PROBES
                        Subsample to at most this many probes per window
                        before fitting.
  --save-figure SAVE_FIGURE
                        Filename to save figure (e.g. motif_plot.png)
  --holm                With --best-pval, use SNV fits and within-SNV Holm
                        correction (ALT AFF and combined REF/ALT RAND
                        families). Outputs compact SNV TSV with adjusted pval
                        and raw_pval; includes flanking windows. This does not
                        correct across the whole region.
  --rand-n RAND_N       RAND background size for --holm (default: 500)
  --diagnostics         Append SNV diagnostics in --best-pval --holm mode
