SPiDR — System processor in Data Research

Multivariate biomedical
analysis, made accessible.

Empowering scientists to uncover what their data is telling them.

SPiDR integrates data analysis from data cleaning to primary analysis to machine-learning–based data mining to pathway analysis, and finally produces publication-ready figures, into a single point-and-click interface — no coding required.

Explore features → View pricing In development, contact us for free trail access

1 · Data prep

Data processing & QC

Upload, merge, rename, and clean multi-assay datasets. Automated sample ID mapping, technical replicate averaging with SD quality control, and negative-control baseline subtraction.

Luminex · ELISA · Flow · RNAcount

2 · Fold-Change calculation

Fold change calculation

Paired per-subject fold change (post/baseline) for longitudinal designs, or group-mean reference normalization. Automatic timepoint matching and missing-data handling.

Paired subject · By negative-control group

3 · Statistics

Statistical analysis

Wilcoxon/Mann-Whitney and ANOVA with Tukey HSD across all analytes. Benjamini-Hochberg, Bonferroni, and Holm corrections for multiple comparisons.

Raw p-value · Conditional p-value adjustment

4 · Univariate Visualization

Univariate plotting

Box plots, violin plots, and smooth dose-response curves with built-in pairwise significance brackets. Single or multi-panel grid layouts with per-group custom colors.

Univariate · Multi-panel

5 · Heatmapping

Heatmap visualization

Publication-quality heatmaps with Z-score scaling, hierarchical clustering, column splitting by condition, and fully customizable annotation color tracks.

Heatmaps · Z-score

6 · Volcano Plotting

Volcano plots

Correlation volcano and classic fold-change volcano. Custom category color groups for highlighting analyte classes with publication-ready labeling.

Correlation (Spearman / Pearson / Kendall) · Fold change

7 · Euler/Venn

Euler diagrams

Area-proportional overlap diagrams showing which analytes meet significance thresholds across multiple targets or conditions.

Venn · Correlation or fold-change

8 · Predictive Modeling

PCA, PLS-DA & PLS-R

Unsupervised or LASSO-selected feature-supervised dimensionality reduction and classification, predicting conditional separation.

Machine learning · LASSO-PLSDA / PLSR

9 · Parameters Determination

Sweep analysis

Systematically test every combination of latent variables, LASSO threshold, and alpha to find optimal PLS-DA and PLS-R models.

Parameter optimization for PLS-DA / PLS-R

10 · Correlation network

Constellation networks & chord diagrams

Correlation-based network graphs with LASSO-selected or manual feature sets. Chord diagrams with user-defined category sectors and directional edge coloring.

Correlation network · Manual or LASSO-based

11 · NAb or PK/PD