v2.2.0

cerebroAppLite 2.2.0

Trekker single-cell spatial mapping

• New page: Trekker. A standalone top-level tab (peer of Spatial) for Curio
  Bioscience / Takara Bio Trekker single-cell spatial-mapping output — real single
  nuclei × whole transcriptome, with positions inferred from bead spatial barcodes
  and (usually) no matched histology image. It appears conditionally, only when the
  loaded .crb carries a trekker slot.
• Physical space and transcriptome space, linked. Because every nucleus has
  both a spatial and a UMAP position, the two scatterplots are shown side by side
  and cross-linked: a box- or lasso-select in one pane highlights the same nuclei
  in the other, and hovering a nucleus rings the same cell in both panes so its
  location reads off instantly. A toolbar matching the app's plotly modebar
  (box / lasso select, pan, zoom, reset, download) sits over the panes. The View
  control switches between side-by-side, a single enlarged Spatial-only or
  UMAP-only pane, and a Transition view that animates each nucleus from its UMAP
  position to its physical position. Colour by cell type, cluster, or any
  of the whole-transcriptome genes, and use the Group filters panel (the same
  per-grouping pickers as the projection tabs) to restrict the view to selected
  cell types or clusters.
• Positioning evidence is auditable. Trekker positions are inferred, so the page
  surfaces the vendor's per-nucleus positioning-evidence images (the bead-barcode
  cloud plus a UMI knee plot) for the sampled nuclei, and a Cell inspector reports
  each nucleus's identity together with the real physical-neighbour cell-type
  counts within a chosen radius (not a deconvolution estimate).
• Colour the physical map by any per-cell value — analysis, not just a view.
  Beyond cell type / cluster / gene, the page colours by cross-space metrics
  computed on the full positioned set — spatial-neighbourhood purity and
  expression-vs-physical neighbourhood concordance (who forms tight anatomical
  domains vs. who is dispersed or infiltrating, with a per-cell-type summary and
  the honest reminder that in a healthy brain low microglial purity is baseline
  tiling, not activation) — and by any numeric per-cell meta column the object
  carries (pseudotime, a signature/module score, velocity magnitude, a signaling
  score), so an existing single-cell analysis result gains a physical-space
  projection with no page change. The demo ships a myelination signature score as
  a worked example. Only Trekker can do this: it needs true single-cell identity
  and true physical position for the same nuclei.
• Canonical coordinates. The panes use the vendor's Location CSV, the canonical
  coordinate authority. The generic @images slot is axis-transposed and the
  SPATIAL reduction is y-mirrored relative to it; the vignette documents that
  discrepancy so the tissue is never silently drawn rotated.
• Honest QC. Positioning QC is shown in the vendor's own field names (a missing
  metric stays missing); "confidently positioned" is disclosed as including
  vendor-salvaged multi-location nuclei (labelled vendor_confidently_positioned);
  values below the vendor's reference range are flagged without adjudicating sample
  usability; and Moran's I is the upstream vendor value, labelled and never mixed
  with Cerebro's own.
• Data class. Cerebro_v1.3 gained an optional trekker slot with
  addTrekker() / getTrekker(); the getter is backward-compatible with older
  .crb files that predate the field.
• Demo data and vignette. A real, down-sampled demo .crb
  (demo_trekker.crb, from the smallest official Trekker bundle: 2,532 nuclei ×
  all 21,374 genes, with positioning-evidence images embedded) and a runnable
  vignette, "Trekker single-cell spatial mapping: from a vendor bundle to an
  interactive app", covering the registration-gated download, the bundle
  contents, and the reproducible build (data-raw/build_trekker_demo.R).

What's Changed

• feat(trekker): single-cell spatial-mapping page (2.2.0) by @duocang in #87

Full Changelog: v2.1.1...v2.2.0