Input format
CSV or TSV. First row = column IDs (e.g. samples), first column = row IDs (e.g. features/genes), remaining cells numeric. Blank / NA cells are handled pairwise.
Between
Correlate the columns (sample–sample, typical QC) or the rows (feature–feature, e.g. gene co-expression).
Method
Pearson (linear), Spearman (rank / monotonic), or Kendall τ-b (rank, robust to outliers, slower). Coefficients match scipy.
Clustering
Hierarchical clustering reorders variables so correlated blocks group together (average/complete/single linkage on 1−r, or 1−|r| to group by strength). A dendrogram is drawn on top.
Significance
Two-sided p-values, Benjamini–Hochberg FDR correction across all pairs. Stars: * <0.05, ** <0.01, *** <0.001. Toggle raw p vs BH q.
Missing data
Each correlation uses only the observations present in both variables (pairwise-complete); the pair's n is shown on hover.
Export
PNG honors the DPI selector; SVG is vector; Copy puts a PNG on the clipboard.
