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1.3.6 when the variance of error is 0, stop the null model fitting
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DESCRIPTION

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Package: SAIGE
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Type: Package
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Title: Efficiently controlling for case-control imbalance and sample relatedness in single-variant assoc tests (SAIGE) and controlling for sample relatedness in region-based assoc tests in large cohorts and biobanks (SAIGE-GENE+)
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Version: 1.3.5
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Date: 2024-04-23
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Version: 1.3.6
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Date: 2024-05-27
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Author: Wei Zhou, Zhangchen Zhao, Wenjian Bi, Seunggeun Lee, Cristen Willer
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Maintainer: SAIGE team <saige.genetics@gmail.com>
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Description:an R package that implements the Scalable and Accurate Implementation of Generalized mixed model that uses the saddlepoint approximation (SPA)(mhof, J. P. , 1961; Kuonen, D. 1999; Dey, R. et.al 2017) and large scale optimization techniques to calibrate case-control ratios in logistic mixed model score tests (Chen, H. et al. 2016) in large PheWAS. It conducts both single-variant association tests and set-based tests for rare variants.
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RoxygenNote: 7.1.2
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NeedsCompilation: yes
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Encoding: UTF-8
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Packaged: 2024-02-06 EST
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Packaged: 2024-05-27 EST

R/SAIGE_fitGLMM_fast.R

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#Y = eta - offset + (y - mu)/mu.eta
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#sqrtW = mu.eta/sqrt(family$variance(mu))
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if(tau[1]<=0){
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stop("ERROR! The first variance component parameter estimate is 0\n")
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}
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#if(tau[1]<=0){
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# stop("ERROR! The first variance component parameter estimate is 0\n")
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#}
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if(tau[2] <= 0) break
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if(tau[1]<=0 | tau[2] <= 0) break
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if(max(abs(tau - tau0)/(abs(tau) + abs(tau0) + tol)) < tol) break

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