Create publication-ready dot plots from grouped experimental data.
Upload raw observations, describe the comparison you need, then generate a clean AI-made PNG with individual points, group labels, summaries, and optional annotations.
Upload data and describe the AI chart you need.
Costs 5 credits. Uses your uploaded data and prompt to generate a publication-ready PNG.
Preview
Aspect ratio: 16:9
These are sample previews. Upload your dataset to generate your own dot plot.
Use these examples as visual directions for raw observations, grouped comparisons, QC ranges, and manuscript-ready dot plots.
Prompt
Based on the uploaded treatment_response_points.csv file, create a publication-ready dot plot comparing individual response values across control, low-dose, high-dose, and combination groups. Use light jitter, median bars, readable group labels, and concise significance annotations.
Prompt
Based on the uploaded cell_viability_replicates.xlsx file, create a dot plot showing replicate-level cell viability across untreated, drug A, drug B, and combination conditions. Include all observations, show mean with error bars, and use a clean scientific palette.
Prompt
Based on the uploaded protein_marker_scores.tsv file, create a grouped dot plot comparing marker scores across healthy, early-stage, and advanced disease cohorts. Show individual samples, sample sizes, median indicators, and clear y-axis units.
Prompt
Based on the uploaded single_cell_cluster_values.csv file, create a dot plot summarizing marker intensity across cell clusters. Use compact jittered points, separate cluster labels, subtle color coding, and a clean legend for control versus treated samples.
Prompt
Based on the uploaded batch_qc_replicates.xlsx file, create a dot plot comparing replicate values across Batch 1, Batch 2, Batch 3, and Batch 4. Highlight the acceptable QC range, show outliers, and keep the figure suitable for a lab quality-control report.
Prompt
Based on the uploaded time_point_measurements.csv file, create a dot plot showing measurements across baseline, 24 hours, 48 hours, and 72 hours. Show individual observations, connect group medians with a subtle trend line, and label the time axis clearly.
Add CSV, TSV, TXT, or Excel observations with a numeric value column and optional group labels.
Tell SciFigure AI the grouping, jitter, summaries, error bars, annotations, and palette you need.
Create a clean dot plot, review the result, then download PNG for papers and slides.
It turns individual observations into a clean dot plot that shows every data point while preserving group comparisons, summary cues, sample sizes, and readable labels.
A numeric value column is required. Category, group, label, or series columns can organize the points.
Use a dot plot when raw observations matter, especially for small or moderate sample sizes.
Yes. Describe the summary marker you need, such as median bars, mean with SD, or mean with SEM.
Yes. Use a group column for treatments, cohorts, batches, time points, or conditions.
Yes, but always verify data mapping, units, labels, statistics, and captions before submission.
Generate dot plots, box plots, violin plots, and other research-ready visualizations with SciFigure AI.
