# How to analyze genetic data that includes relatives? **URL:** \ **Category:** Analyzing and Reusing Data\ **Tags:** biostatistics, genetic-data, how-to\ **Created:** [March 7, 2024, 2:52pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385 "2024-03-07T14:52:51Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![fbbriggs](https://sea1.discourse-cdn.com/michaeljfox/user_avatar/rcop.michaeljfox.org/fbbriggs/32/54_2.png) [@fbbriggs](https://rcop.michaeljfox.org/u/fbbriggs)\ **Post date:** [March 7, 2024, 2:52pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/1 "2024-03-07T14:52:51Z")
Does anyone have suggestions? I have a relative small dataset for a rare phenotype, as a result I would like to maximize the sample size retained (versus randomly retaining only one relative as it standard in traditional GWAS)? I have heard of REGENIE and GENESIS? Any experience or other suggestions? ---
**Author:** ![jgottesman](https://sea1.discourse-cdn.com/michaeljfox/user_avatar/rcop.michaeljfox.org/jgottesman/32/46_2.png) [@jgottesman](https://rcop.michaeljfox.org/u/jgottesman)\ **Post date:** [March 11, 2024, 6:43pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/2 "2024-03-11T18:43:54Z")
@hirotaka or @mike any thoughts? ---
**Author:** ![mike](https://avatars.discourse-cdn.com/v4/letter/m/58f4c7/32.png) [@mike](https://rcop.michaeljfox.org/u/mike)\ **Post date:** [March 11, 2024, 7:01pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/3 "2024-03-11T19:01:09Z")
Any mixed model that incorperates kinship from GCTA to regenie will do the job. ---
**Author:** ![hirotaka](https://sea1.discourse-cdn.com/michaeljfox/user_avatar/rcop.michaeljfox.org/hirotaka/32/58_2.png) [@hirotaka](https://rcop.michaeljfox.org/u/hirotaka)\ **Post date:** [March 11, 2024, 7:28pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/4 "2024-03-11T19:28:31Z")
I haven’t conducted analyses that include relatives, but these softwares ([https://yanglab.westlake.edu.cn/software/gcta/#Overview](https://yanglab.westlake.edu.cn/software/gcta/#Overview)) and GENESIS seem capable of such analyses with GRM. ---
**Author:** ![paularp](https://sea1.discourse-cdn.com/michaeljfox/user_avatar/rcop.michaeljfox.org/paularp/32/52_2.png) [@paularp](https://rcop.michaeljfox.org/u/paularp)\ **Post date:** [April 12, 2024, 1:14am UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/5 "2024-04-12T01:14:23Z")
I believe @peixott is currently using SAIGE! [Home | SAIGE](https://saigegit.github.io/SAIGE-doc/) ---
**Author:** ![peixott](https://sea1.discourse-cdn.com/michaeljfox/user_avatar/rcop.michaeljfox.org/peixott/32/299_2.png) [@peixott](https://rcop.michaeljfox.org/u/peixott)\ **Post date:** [April 12, 2024, 1:45pm UTC](https://rcop.michaeljfox.org/t/how-to-analyze-genetic-data-that-includes-relatives/385/6 "2024-04-12T13:45:53Z")
> [@fbbriggs](#): > > I have heard of REGENIE and GENESIS? Any experience or other suggestions? > > > [@](#): > > > > I haven’t conducted analyses that include relatives, but these softwares ([https://yanglab.westlake.edu.cn/software/gcta/#Overview](https://yanglab.westlake.edu.cn/software/gcta/#Overview)) and GENESIS seem capable of such analyses with GRM. > > I am using SAIGE and TRACTOR. In a recent benchmark [1] showed that SAIGE is the best in type of Type-I error rate and TRACTOR is the most powerful analysis for admixed (and LARGE-PD is all about admixed people). > > SAIGE allows you to include the genetic relationship matrix (GRM) in the model, so you do not remove anyone based on relationship. TRACTOR does not use GRM, so we need to remove related people. To do this I use NAToRA [2] (which I am the creator, so I may be biased) that is better than PLINK and KING. > > I hope to help > Thiago Peixoto Leal > > Ref: > [1] DOI: 10.1093/bib/bbad437 > [2] DOI: 10.1016/j.csbj.2022.04.009