Batch analysis

Run a list of genes or UniProt IDs with optional coordinates or region discovery; get the same metric layers as elsewhere in DisCanVis, aggregated per row. Programmatic access: API (batch endpoint).

Batch API
adjustAnalysis scope

Full protein = one row per identifier, or — with motif search — regex/PSSM hits over the whole sequence. Regions = annotation discovery (ELM, Pfam, …) when coordinates are missing.

travel_exploreRegion discovery

When a line has no coordinates, regions are taken from annotations, PEM, or motif search (regex / PSSM).

Step 1
First row can be one-letter amino-acid headers (tab- or comma-separated). Otherwise values use order ARNDCQEGHILKMFPSTWYV. Optional comment line: # min_score: 1.5
filter_altCohort filters

Optional: disorder cutoff and island pathogenicity for motif hits. Expand when you need them.

Step 2
Min % disordered %
Uses combined disorder (≥2.0) fraction within each region. Turn off to include ordered regions.
Choose whether the motif “island” is defined by pathogenicity scores or by a conservation peak.

Keep hits if mean AlphaMissense in the motif is ≥ Δ above the flank reference (max or mean of N- and C-windows) or core mean AM ≥ threshold. Default: each flank width = motif length (clamped at termini); reference = max flank (stronger side).

Keep hits if mean conservation in the motif is ≥ Δ above the flank reference or core ≥ threshold. Default flanks follow motif length per side.

inputInput list
Type at least 2 characters, choose a row with a GO:… id. The list below fills with main-isoform Gencode IDs (same set as Statistics → dynamic GO), not raw annotation rows.
Uses the same PPI union as Statistics (IntAct / HIPPIE / BioGRID-style rows in Interactions_Summary). Fills main-isoform Gencode accessions for the hub plus direct partners.
Optional: two integers after the ID for explicit coordinates.
view_columnRequested columns

Toggle layers with the same pill style as Summary coverage badges — each chip is one output column.

Step 3

visibility Output columns follow Summary track colours (mutations, disease, motifs, disorder, conservation).

local_fire_department Mutations — cancer

Request somatic layers by class (missense / frameshift / indel), same buckets as cohort statistics.

Missense
Frameshift
Indel
medical_services Mutations — disease
hive Domains, motifs & PTMs
analytics Pathogenicity, conservation, disorder & binding

Default pathogenicity is AlphaMissense only; add conservation, extra disorder tracks, or ANCHOR when needed. Binding defaults to AIUPred.

Pathogenicity
dbNSFP-style (region mean over variant table)
Conservation
Disorder & structure
Binding
Programmatic access

Same analysis via POST /api/v1/batch/analyze/ — see API documentation.