User Guide

Guided use of NENIA

Follow three visual walkthroughs for moving from eQTL-guided MR evidence to single-cell gene expression, searching one gene across datasets, running bidirectional trait Mendelian randomization, and exporting AI-ready Markdown for downstream interpretation.

eQTL & SC

Choose an MR result set, review summary plots, open a gene, inspect single-cell atlas evidence, and export an AI report Markdown file.

Gene browse

Search one target gene, compare available datasets, export tables, and download AI-ready Markdown for interpretation.

Bidirectional MR

Move from phenotype selection to bidirectional evidence review, then export a compact Markdown report for LLM analysis.

Walkthrough 01

eQTL & SC

Use this workflow to start from eQTL-guided MR evidence, continue into single-cell gene expression inspection, and export a Markdown context file for AI-assisted interpretation.

Step 1

Open the eQTL & SC workflow

Use the eQTL & SC navigation item or the home-page entry card to enter the combined MR and single-cell workspace.

eQTL and single-cell tutorial step 1 — The top navigation and home-page card both open the eQTL and single-cell workflow.

Step 2

Choose a dataset and filters

Select the MR result set, then set the significance criteria, threshold, and MR method before running the query.

eQTL and single-cell tutorial step 2 — Dataset cards and query controls define the filtered eQTL-MR result set.

Step 3

Review summary plots

Review the volcano, forest, and sensitivity panels, highlight selected genes, and export figures when needed.

eQTL and single-cell tutorial step 3 — Volcano, forest, and sensitivity panels summarize the filtered eQTL-MR records.

Step 4

Open a gene from the ranked table

Use the ranked MR table to move from a significant gene row into the single-cell analysis page.

eQTL and single-cell tutorial step 4 — Clicking a gene connects MR evidence with the downstream single-cell view.

Step 5

Set atlas context filters

Select one or more organs and cell types, then compare NENs and normal tissue contexts before interpreting the selected gene expression views.

eQTL and single-cell tutorial step 5 — Context filters define the organ, status, and cell-type scope used by the downstream single-cell panels.

Step 6

Review single-cell figures

Use the single-cell figure panels to compare tumor and normal tissue views and download the relevant plots.

eQTL and single-cell tutorial step 6 — Feature, density, violin, dot, and composition views are shown together for the selected gene.

Step 7

Use GPT-5.5 or export Markdown

Use the built-in GPT-5.5 panel to analyze results or ask follow-up questions up to three times per day. The first request is fixed as result interpretation with a prepared prompt; for deeper analysis, download the structured Markdown output and submit it directly to any LLM.

eQTL and single-cell tutorial step 7 — The GPT-5.5 panel provides guided result interpretation, while the Markdown export provides the structured LLM-ready output we designed.

Walkthrough 02

Gene browse

Search a gene directly, compare evidence across datasets, export filtered gene-level results, and prepare an AI-readable Markdown report.

Step 1

Open the Gene browse workflow

Use the Gene browse navigation item or the home-page entry card when the analysis starts from a known gene.

Gene browse tutorial step 1 — The top navigation and home-page card both open the gene-first workflow.

Step 2

Choose a gene, datasets, and filters

Enter a target gene, select the datasets to summarize, then set the significance criteria, threshold, and MR method before running the query.

Gene browse tutorial step 2 — Gene and dataset controls define the cross-dataset MR summary before the query runs.

Step 3

Update the gene or dataset scope

Use the results-page controls to reselect the target gene or dataset set, then rerun the browse query when the evidence scope needs refinement.

Gene browse tutorial step 3 — The results view keeps gene and dataset controls available above the gene-level MR evidence table.

Step 4

Review summary and single-cell figures

Review eQTL-MR summary figures, inspect target-gene expression across selected organs and cell types, compare NENs with normal tissue, and download the relevant figures.

Gene browse tutorial step 4 — MR summary plots and single-cell atlas panels stay together for interpretation and export.

Step 5

Use GPT-5.5 or export Markdown

Walkthrough 03

Bidirectional MR

Explore trait-oriented Mendelian randomization evidence for phenotypes related to neuroendocrine neoplasms, then export a compact AI-ready report context.

Step 1

Open the Bidirectional MR workflow

Use the Bidirectional MR navigation item or the home-page entry card when the analysis starts from trait-oriented MR evidence.

Bidirectional MR tutorial step 1 — The top navigation and home-page card both open the bidirectional MR workflow.

Step 2

Choose a dataset and filters

Select the dataset to explore, filter instrumental variables by the threshold, set the significance criteria and threshold, choose an MR method, and run the analysis.

Bidirectional MR tutorial step 2 — Dataset cards and query controls define the threshold, significance filter, and MR methods for the run.

Step 3

Review summary plots

Review the bidirectional MR result table and plots, highlight selected features, and download the volcano, forest, and sensitivity figures.

Bidirectional MR tutorial step 3 — Volcano, forest, and sensitivity panels summarize selected bidirectional MR records without a gene-level single-cell step.

Step 4