2. Step A — Construct `mcDETECT` and understand every parameter

Step A1. Import the class:

from mcDETECT.model import mcDETECT

Step A2. Read the parameter list below in order. Each entry matches one argument of mcDETECT(...).

type — "discrete" or "continuous"; see Section 1.
transcripts — Full transcript DataFrame; column requirements are in Section 1.
gnl_genes — list[str]: all granule / synaptic marker genes to run DBSCAN on.
nc_genes — list[str] or None. If None, detect() skips negative-control filtering. Otherwise nc_filter runs at the end of detect().
eps — DBSCAN neighborhood radius in coordinate units (3D).
minspl — If None, poisson_select(gene) sets per-gene min_samples from tissue area and background density. If an integer, that value is used for all genes (as in 3_detection.py with minspl=3).
grid_len — Bin width when estimating tissue area for the Poisson model (not the spot grid in downstream notebooks).
cutoff_prob — Quantile for the Poisson background (used when minspl is None).
alpha — Multiplier on expected local density inside π eps² when selecting min_samples.
low_bound — Lower floor for automatic min_samples and minimum number of unique transcript positions per DBSCAN cluster before the cluster is skipped.
size_thr — Discard spheres whose minimum enclosing ball has radius ≥ size_thr. Use a very large value (e.g. 1e5) for a “no radius cap” exploratory run.
in_soma_thr — Discard spheres with in-soma ratio ≥ in_soma_thr. Use a value slightly above 1 (e.g. 1.01) to effectively disable.
l — Scales center–center distance vs. sum of radii when resolving overlaps between spheres from different genes.
rho — Threshold pairing with l for deciding when two spheres “intersect” vs. nest for merge logic in merge_sphere.
s — Scales the radius of a new sphere after merging two overlapping spheres (miniball over combined points).
nc_top — When nc_genes is set, only the top nc_top negative-control genes by transcript count enter the NC filter.
nc_thr — Maximum allowed ratio of NC transcripts to total transcripts inside the sphere; spheres above this are removed. Use None to keep all spheres but still compute nc_ratio if applicable.
merge_genes — If True, granule markers are collapsed to a single pseudo-marker column for detection (see model.py).
merged_gene_label — Label used for that pseudo-marker when merge_genes=True.

Step A3. Instantiate without inline comments — parameters are documented above:

mc = mcDETECT(
    type="discrete",
    transcripts=transcripts,
    gnl_genes=syn_genes,
    nc_genes=nc_genes,
    eps=1.5,
    minspl=3,
    grid_len=1,
    cutoff_prob=0.95,
    alpha=10,
    low_bound=3,
    size_thr=4.0,
    in_soma_thr=0.1,
    l=1,
    rho=0.2,
    s=1,
    nc_top=20,
    nc_thr=0.1,
    merge_genes=False,
    merged_gene_label="merged",
)

The same hyperparameter names apply to rough vs fine runs; only the values of nc_genes, size_thr, in_soma_thr, and related flags change; see Section 3.

Next: Step B — Granule detection

2. Step A — Construct mcDETECT and understand every parameter

2. Step A — Construct `mcDETECT` and understand every parameter