Variant Analysis Tool

Upload a TSV to parse and review variant rows in the table below (data comes from your file).

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Analysis Results

Variant ID Location Type Gene Clinical Significance Population MAF Protein Impact Publications

How to use the Variant Analysis tool

This tool reads a TSV you upload and renders variant rows in a table. It does not query ClinVar, gnomAD, or other services—every value must already be in your file. Maximum upload size is 15 MB.

  1. Prepare the TSV. Use tab-separated text with a header row and one variant per row. Column order must match: variant ID, location, type, gene, molecular consequences, clinical significance, then MAF columns (1000 Genomes, ESP, ExAC), then publications (comma-separated within a cell if needed). The first column must contain a non-empty variant identifier; rows without an ID are skipped.
  2. Choose file. Click Choose TSV File and select .tsv or .txt. Confirm the filename appears; then enable Analyze Variants.
  3. Processing options. Check or uncheck Clinical Significance, Population Frequency, Protein Impact, and Publications to show or hide those columns in Analysis Results.
  4. Batch size. Select 10, 25, 50, or 100 variants per server chunk. Large files are processed in batches with a short pause between chunks; for small files the choice has little effect.
  5. Run analysis. Click Analyze Variants. Watch the status area for parse errors (wrong delimiter, empty file, size over limit).
  6. Interpret the table. Population MAF shows one value from your MAF columns: first non-empty among 1000G, ExAC, then ESP. Protein Impact maps from your molecular consequences column.
  7. Citation. APA, MLA, and BibTeX strings are under How to Cite This Tool (below the FAQ in this tool).

Scope: Not a VCF importer—convert to this TSV layout first. No live re-annotation. For research and teaching, not clinical reporting.

Frequently Asked Questions

What file format should I use for variant analysis?

Use a tab-separated file with a header row and one variant per row. Expected column order: variant ID, location, type, gene, molecular consequences, clinical significance, 1000 Genomes MAF, ESP MAF, ExAC MAF, publications (comma-separated within the cell if needed). The first column must contain a variant identifier (for example an rs ID). This tool does not call external annotation APIs; it displays the values you supply.

What does the clinical significance column show?

It shows the text from your clinical significance column after parsing the TSV. Prepare that column with your own classifications or notes from sources you trust; the app does not query ClinVar or other databases automatically.

What is population frequency (MAF) here?

The table shows a single MAF value taken from your file: it prefers the 1000 Genomes MAF column, then ExAC, then ESP, when those cells are filled. It reflects whatever you encoded in the TSV, not a live lookup from gnomAD or other servers.

How is protein impact determined?

The Protein Impact column displays the molecular consequences field from your row (for example consequence terms or notes you exported from another pipeline). The tool does not run SIFT, PolyPhen, or CADD on the server.

Why should I select a batch size?

The server walks your rows in chunks of that size and waits briefly between chunks. For very large files this spreads work over time; for smaller files the choice has little effect. There is no separate “live” analysis step per batch beyond reading your data.

How to Cite This Tool

APA Format

Priyam, J. (2025). Jyotsna's NCBI Tools - Variant Analysis Tool. DOI: https://doi.org/10.5281/zenodo.15069907

MLA Format

Priyam, J. "Jyotsna's NCBI Tools - Variant Analysis Tool." 2025, DOI: https://doi.org/10.5281/zenodo.15069907. Accessed April 23, 2026.

BibTeX Format

@software{10_5281_zenodo_15069907, author = {Priyam, J.}, title = {Jyotsna's NCBI Tools - Variant Analysis Tool}, year = {2025}, version = {1.0.0}, doi = {https://doi.org/10.5281/zenodo.15069907}, url = {https://ncbi.jyotsnapriyam.com/variant-analysis}, note = {Accessed: April 23, 2026} }