Table of Contents

• Introduction
• Citation
• How to install and run GATE
• UK Biobank GWAS Results
• Log for fixing bugs
• Notes for users before running jobs

Introduction

Current version is 0.42.1

GATE (Genetic Analysis of Time-to-Event phenotypes) is an R package with Scalable and accurate genome-wide association analysis of censored survival data in large scale biobanks using frailty models.

GATE performs single-variant association tests for time-to-event endpoints. GATE uses uses the saddlepoint approximation (SPA)(mhof, J. P. , 1961; Kuonen, D. 1999; Dey, R. et.al 2017) to account for heavy censoring rates.

GATE is based on joint work by Rouank Dey and Wei Zhou.

Citation

How to install and run GATE (Similar to SAIGE and SAIGE-GENE)

https://github.com/weizhouUMICH/SAIGE/wiki/Genetic-association-tests-using-SAIGE

The docker image can be found in the docker hub wzhou88/saige.survival:0.42.1

Notes for users before running jobs

• After installation, the package needs to be called as SAIGE (will update)

• Currently, the only difference between this and the regular SAIGE job is that for step1, two additional arguments are used

eventTimeCol = “”,
eventTimeBinSize = 1

and

traitType = “survival”

eventTimeCol is the column name for the event time, e.g. age of diagnosis eventTimeBinSize is used to set the bin size for evene times. eventTimeBinSize=1 means the bin size will be 1 and if eventTimeBinSize is not specified, raw event time values will be used

Logs for bug fixing

• 0.42.1 (August-19-2021) trying to fix the error X1_fg %*% Z : non-conformable argument

• 0.42 (July-14-2021) fix the "AF > 0.5" error when input file is VCF

• 0.41 (January-11-2021) fix the error from the merging branches