GengruiZhu

GengruiZhu / KmerGenoPhaser

Public

K-mer specificity + SNP/ML + autoencoder pipeline for ancestry block phasing in allopolyploid genomes. Three modules (supervised / snpml / unsupervised) + karyotype visualization. Supports sugarcane, wheat, and other polyploids.

12
1
100% credibility
Found Mar 20, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

KmerGenoPhaser is a bioinformatics toolkit for identifying and visualizing ancestry blocks in polyploid genomes using k-mer frequencies and SNP data across supervised, unsupervised, and diagnostic modes.

How It Works

1
🔍 Discover KmerGenoPhaser

You find this helpful tool on GitHub while searching for ways to map ancestry in hybrid plant genomes.

2
📦 Get everything ready

Download the kit and follow simple steps to set up your personal analysis workspace on your computer.

3
📊 Prepare your genome data

Gather your plant genome sequence and related samples, like parent plants, to feed into the tool.

4
Pick your analysis path
👨‍🔬
Guided with markers

Use info from known parent plants to label ancestry blocks clearly.

🤖
Auto-discovery

Let the tool figure out ancestry patterns on its own from the genome.

🧬
DNA spot focus

Zoom in on key DNA differences between groups for precise mapping.

5
🚀 Launch the analysis

Hit start and watch as it processes your data, building a picture of your genome's family tree.

6
🖼️ View beautiful maps

Open colorful diagrams showing ancestry blocks along each chromosome, like a family portrait.

🎉 Unlock genome secrets

Celebrate as you now see exactly which parts of your hybrid plant come from which ancestors.

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Star Growth

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AI-Generated Review

What is KmerGenoPhaser?

KmerGenoPhaser is a Python pipeline for ancestry block phasing in allopolyploid genomes like sugarcane and wheat. It combines k-mer specificity, SNP/ML diagnostics, and autoencoder-based unsupervised learning across three modular pipelines to map subgenome ancestry blocks, producing idiogram-style karyotype visualizations. Developers get CLI-driven workflows that turn raw genomes into phased ancestry maps without manual scripting.

Why is it gaining traction?

It stands out by tackling polyploid phasing where standard tools fail, offering supervised k-mer filtering, SNP/ML for diagnostic sites, and autoencoder modules that adapt to noisy data. The conda-based install with smoke tests and symlink setup gets you running fast, while outputs like merged PDF karyotypes and block TSvs make results publication-ready. Niche polyploid researchers appreciate the end-to-end automation over fragmented scripts.

Who should use this?

Plant genomicists analyzing sugarcane, wheat, or other polyploids for breeding ancestry inference. Bioinformaticians needing quick SNP/ML or k-mer pipelines for block-level phasing without building custom autoencoders. Teams visualizing complex genomes via karyotype plots for subgenome identification.

Verdict

Worth trying for polyploid ancestry work despite 12 stars and 1.0% credibility score—docs are README-focused but install scripts and tests ease onboarding. Early-stage maturity means expect tweaks for production, but it's a solid niche starter.

(198 words)

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