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JanusX

CLI Guide | Core API Guide | Zea Eureka

Python License

Overview

JanusX (Joint Association and Novel Utility for Selection) is a GWAS and genomic selection toolkit that combines:

  • Rust-accelerated kernels (PyO3 extension)
  • Python analysis modules
  • A Rust launcher (jx) for runtime/toolchain management and pipeline orchestration
       _                      __   __
      | |                     \ \ / /
      | | __ _ _ __  _   _ ___ \ V /
  _   | |/ _` | '_ \| | | / __| > <
 | |__| | (_| | | | | |_| \__ \/ . \
  \____/ \__,_|_| |_|\__,_|___/_/ \_\ Tools for GWAS and GS
  ---------------------------------------------------------

Main capabilities:

  • GWAS: LM, LMM, FastLMM, LRLMM, FarmCPU
  • Genomic selection: GBLUP, adBLUP, rrBLUP, BayesA/B/Cpi, and ML models (RF/ET/GBDT/XGB/SVM/ENET)
  • Streaming genotype IO for VCF/HMP/PLINK/TXT/NPY
  • Post-analysis workflows: postgwas, postgarfield, postbsa
  • Utility workflows: grm, pca, gformat, gmerge, hybrid, adamixture, webui, sim, simulation
  • Launcher pipelines: fastq2vcf, fastq2count

jx & jxpy

JanusX provides two command entry styles:

  • jx (Rust launcher): manages runtime/update/toolchain and supports all launcher modules
  • jxpy (Python package entry): runs Python-side modules directly

Practical difference:

  • fastq2vcf and fastq2count are launcher-only (jx)
  • launcher-only flags (-update/-upgrade/-list/-clean/-uninstall) are not available in jxpy

Installation

Option A: launcher install (recommended for end users)

Download installer assets from Releases:

Then run installer:

# Linux
./JanusX-vX.Y.Z-linux-x86_64.run

# macOS
./JanusX-vX.Y.Z-darwin-universal.command

On Windows, double click or run the .exe installer.

After install:

jx -v
jx -list module

Option B: Python package install (API-first / development)

pip install janusx
# command entry: jxpy (version>=3.14) or jx (version<3.14)
  • If you only need a turnkey CLI environment with pipeline tooling, prefer launcher install.

Quick start

1) GWAS

jx gwas -vcf example/mouse_hs1940.vcf.gz -p example/mouse_hs1940.pheno -lmm -o test

overview

2) Post-GWAS

jx postgwas -gwasfile test/mouse_hs1940.test0.add.lmm.tsv -manh -qq -thr 1e-6 -o testpost

ldblock

3) Genomic selection

jx gs -vcf example/mouse_hs1940.vcf.gz -p example/mouse_hs1940.pheno -GBLUP -cv 5 -o testgs
* Genomic Selection for trait: test0
Train size: 1410, Test size: 530, EffSNPs: 8960
✔︎ GBLUP ...Finished [3.5s]
✔︎ adBLUP ...Finished [10.1s]
✔︎ BayesA ...Finished [32.6s]
✔︎ BayesB ...Finished [34.2s]
✔︎ BayesCpi ...Finished [32.0s]
✔︎ RF ...Finished [1m46s]
✔︎ XGB ...Finished [9m27s]
✔︎ SVM ...Finished [2m05s]
✔︎ ENET ...Finished [9.7s]
Fold Method     Pearsonr Spearmanr     R² h²/PVE time(secs)
   1 GBLUP         0.704     0.671  0.493  0.610      0.531
   1 adBLUP        0.717     0.679  0.512  0.694      2.341
   1 BayesA        0.721     0.695  0.514  0.714      5.307
   1 BayesB        0.722     0.693  0.517  0.667      5.522
   1 BayesCpi      0.699     0.671  0.476  0.672      4.971
   1 RF            0.709     0.702  0.471  0.468      3.055
   1 XGB           0.754     0.733  0.564  0.563      5.231
   1 SVM           0.703     0.664  0.490  0.485      9.027
   1 ENET          0.720     0.704  0.514  0.517      0.274

gsoverview

See full usages in CLI Guide.

4) Get module help

jx <module> -h

Module map

Genome-wide Association Studies (GWAS):

  • grm
  • pca
  • gwas
  • postgwas (Visualization, manh qq ldblock)

Genomic Selection (GS):

  • gs
  • reml (Estimation of broaden heritability and blup values)

GARFIELD:

  • garfield
  • postgarfield

Bulk Segregation Analysis (BSA):

  • postbsa (Visualization, after BSA pipeline)

Pipeline and utility:

  • fastq2count (RNAseq pipeline, launcher-only)
  • fastq2vcf (BSA/Reseq pipeline, launcher-only)
  • adamixture (Based on ADAMIXTURE)
  • hybrid (Generate F1 genotype base on Parents)
  • gformat (Conversion between genotype data formats)
  • gmerge (Merge genotype between samples)
  • webui (Visualization, beta version)

Benchmark:

  • sim
  • simulation

Citation

@article {FuJanusX,
  title = {JanusX: an integrated and high-performance platform for scalable genome-wide association studies and genomic selection},
  author = {Fu, Jingxian and Jia, Anqiang and Wang, Haiyang and Liu, Hai-Jun},
  year = {2026},
  doi = {10.64898/2026.01.20.700366},
  publisher = {Cold Spring Harbor Laboratory},
  URL = {https://www.biorxiv.org/content/early/2026/01/23/2026.01.20.700366},
  journal = {bioRxiv}
}

License

This project is licensed under GNU Affero General Public License v3.0 (AGPL-3.0-or-later). See LICENSE.

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A high-performance, ALL-in-ONE suite for quantitative genetics that unifies genome-wide association studies (GWAS) and genomic selection (GS).

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