Evidence map›Paper›PMID 41648194›Full record

ArticlebioRxiv : the preprint server for biology2026

RAREsim2: Flexible simulation of rare variant genetic data using real haplotypes.

Jessica I Murphy, Ryan Barnard, Megan Null, Audrey E Hendricks

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Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ryan Barnard
Megan Null
Audrey E HendricksORCID 0000-0002-7152-0287

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary: Realistic simulated data is critical for advancing methodological development and optimizing study design in genetics research. However, many genetic simulation tools are unable to replicate the distribution of rare variants or incorporate key genetic information, such as functional annotations and linkage disequilibrium. RAREsim, an accurate rare-variant simulation algorithm that uses real genetic haplotypes, was developed to address these limitations. Here, we introduce RAREsim2, an update that provides both streamlined software and new functionalities for simulating individual-level differences (e.g., cases vs controls, technological or batch effects) and variant-level differences to represent a variety of causal models.We demonstrate RAREsim2's utility with three rare variant association methods (Burden, SKAT, and SKAT-O) across several simulation scenarios: causal variants only in cases, causal variants in both cases and controls, and no causal variants. Type I Error was maintained and the optimal test matched previously known patterns: Burden performed best given a large amount of causal variants with the same direction of effect; SKAT performed best given causal variants with opposite directions of effect. SKAT-O was powerful across all simulation scenarios. We highlight RAREsim2's capabilities to simulate various genetic ancestries (African, East Asian, Non-Finnish European, and South Asian), gene sizes (~20-80 functional rare variants per gene), strengths of association (20%, 40%, 60% functional variants), and proportions of risk variants (1, 0.75, 0.5). Importantly, real genetic regions can be simulated to include known variant functions and disease associations. Ultimately, RAREsim2 offers additional flexibility and ease in simulating a multitude of realistic genetic scenarios. Availability and implementation: The RAREsim2 python package is available at https://github.com/Hendricks-Research-Team/RAREsim2 and the code for the example demonstration is available at https://github.com/JessMurphy/RAREsim2_demo . Contact: jessica.murphy@cuanschutz.edu.

Identifiers

PMID41648194
PMCPMC12871163

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.