Publishable Figs

Licklider produces publication-ready figures directly from your analysis — formatted to the exact specifications of your target journal, with statistical annotations, effect sizes, and confidence intervals embedded automatically. Every visual element is linked to a statistical decision that can be justified to a reviewer.

What are Publishable Figs?

Publishable Figs are high-resolution, editable figures that meet the submission requirements of journals including Nature, Science, Cell, NEJM, and hundreds of society publications. Every figure is generated from the same analysis run that produces your statistical results — guaranteeing perfect reproducibility between the numbers and the visualization.

Figures are not cosmetic. Every visual element — axis ranges, color choices, error bar style, annotation position — is linked to a statistical or methodological decision that Licklider records and can explain. When a reviewer asks "why SEM and not SD?" or "why violin and not bar chart?", the answer is in the audit log.

Distribution & Group Comparison

The most common figure type in experimental biology, psychology, and clinical research. Each figure type comes with mandatory statistical annotation requirements and guards against common display errors (bar charts hiding distributions, SEM mislabeled as SD).

5.1 Overview

All 7 distribution and group comparison figure types with selection guidance.

Box Plot

Median, IQR, whiskers, and outliers — the most space-efficient distribution summary.

Violin Plot

Full distribution shape with kernel density estimation — preferred for n ≥ 20.

Strip / Jitter Plot

Shows every data point — preferred for n < 20, where summaries hide the data.

Bar Chart (Mean ± SEM)

Conditional use only: n must be shown, SEM labeled, individual data overlaid when n < 20.

Histogram

Bin-width optimized, normality annotation optional, frequency vs. density display.

Dot Plot (Estimation)

Gardner-Altman style: raw data with mean difference and 95% CI in a separate panel.

2D Density Contour

Two continuous variables with overlapping group distributions and contour levels.

Correlation & Regression

Figures displaying relationships between continuous variables, with correlation disclosure, regression assumption checks, and mandatory distinction between descriptive and inferential use.

5.2 Overview

All 5 correlation and regression figure types with when-to-use guidance.

Scatter Plot

Pearson / Spearman r with CI, point transparency for overplotting, correlation disclosure.

Regression Plot

Fitted line with confidence band, R², equation, and causation vs. correlation guard.

Bubble Chart

Three-variable encoding with size proportional to n or a third continuous variable.

Confidence Ellipse

95% bivariate confidence ellipse per group — correct group overlap visualization.

Bland-Altman Plot

Method agreement analysis: mean difference, limits of agreement, and clinical acceptability.

Multivariate & Dimensionality

High-dimensional data summaries requiring careful handling of clustering distance metrics, color scale selection, and correct PCA scaling disclosure.

5.3 Overview

All 4 multivariate figure types with parameter disclosure requirements.

Heatmap

Clustering method, distance metric, scaling (row/column/none), and color scale all disclosed.

Parallel Coordinates

Multi-variable profile comparison with axis scaling, group coloring, and missingness handling.

PCA Biplot

Scores + loadings with variance explained per PC and centering/scaling disclosure.

Hierarchical Clustering

Dendrogram with linkage method, distance metric, and optimal k selection criteria.

Clinical & Biomedical

Specialized figures with mandatory statistical content required by clinical journal reporting guidelines — censoring disclosure for KM curves, AUC with CI for ROC, and effect estimates for forest plots.

5.4 Overview

All 4 clinical figure types with CONSORT/STROBE disclosure requirements.

Kaplan-Meier Curve

Survival curve with at-risk table, censoring marks, log-rank p-value, and median survival CI.

ROC Curve

AUC with 95% CI (DeLong method), optimal threshold, sensitivity/specificity at threshold.

Volcano Plot

Fold-change vs. adjusted p-value with multiple testing correction and fold-change threshold disclosure.

Forest Plot

Effect estimates with 95% CI per study/subgroup, heterogeneity I², and pooled estimate.

Composition & Trends

Composition and time-series figures with strong guards against common misuse — pie charts require disclosure when proportions are too similar to distinguish, and line charts require continuity justification.

5.5 Overview

All 3 composition and trend figure types with appropriate-use guards.

Pie / Donut Chart

Conditional use: ≤7 categories, no similarly-sized slices, values labeled. Alternative: stacked bar.

Line Chart (Time Series)

Longitudinal data with within-subject SEM, repeated-measures annotation, and continuity guard.

Stacked Bar Chart

Proportional stacked bars with color palette accessibility check and value label requirement.