Gradient Biotech

Multi-modal profiling

The multimodal_profiling pipeline supports dependency-gated CITE-seq, ATAC, multiome, and cytometry workflows.

CITE-seq

Tabular ADT inputs are normalized with CLR and summarized with:

  • ADT QC
  • protein heatmap values
  • protein-informed clusters
  • joint RNA/protein coordinate fallback when paired rna_/gene_ and adt_/protein_ features are supplied
  • optional per-cell isotype/background correction
  • RNA/protein discordance summaries for immune marker programs
  • CITE-seq phenotype panels using CD marker combinations

Full WNN graph construction and clustering remain dependency-gated. The current fallback is intended for inspectable research summaries, not a replacement for full multimodal graph learning.

ATAC

Tabular peak inputs produce:

  • peak accessibility track rows
  • total accessibility summaries
  • TF motif enrichment cards
  • per-cell accessibility QC with detected peaks, fragment/TSS/nucleosome proxies, and doublet-risk flags when columns are present
  • dependency-free TF-IDF/LSI coordinates
  • marker peaks by group
  • gene activity scores from peak-to-gene annotations
  • peak-to-gene correlation links
  • group coverage rows

Full fragment-file processing, peak calling, motif deviation scoring, footprinting, and genome-browser tracks remain gated behind approved scATAC runtimes such as SnapATAC2.

Multiome

The current workflow provides an integration summary using protein clusters and accessible peaks. Full WNN/multiome graph integration remains gated behind muon.

Cytometry

CSV/TSV event tables support:

  • automated lineage marker gating
  • population frequencies
  • cytometry coordinate fallback
  • FlowSOM-style arcsinh-transformed prototype clustering
  • metacluster assignments and minimum-spanning-tree edges
  • marker heatmap rows by metacluster
  • sample-level metacluster abundance summaries

Binary FCS parsing remains gated behind FlowUtils or flowutils.