Open Zhang-Rui-2018 opened 1 month ago
Hi Zhang Rui,
We are working on the COJO version that uses the LD matrix as input. I will make an announcement on Twitter when it's ready to use.
Best regards, Jian
Jian Yang Professor of Statistical Genetics School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China. T: +86-571-87089837. W: Lab websitehttps://yanglab.westlake.edu.cn/
From: Zhang Rui @.> Reply to: jianyangqt/gcta @.> Date: Saturday 13 July 2024 at 02:29 To: jianyangqt/gcta @.> Cc: Subscribed @.> Subject: [jianyangqt/gcta] Can COJO take LD matrix as input (Issue #85)
Hi! I am trying to run COJO to calculate conditional p-value, and found the toy example with the following command line:
The option --bfile specifies the genotype data which is in plink binary format to calculate LD matrix. I am wondering if I already have the LD matrix, can I use this matrix as the input of COJO. I noticed that SMR has the option --bld which can read LD information from a binary file in BLD format. Besides, SMR can be used to make a BLD file from SNP genotype data. Does COJO have the same option? If so, can I get binary LD file from LD matrix instead of genotype data.
Any insights are highly appreciated! Thank you!
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Got it! Thanks!
Hi! I am trying to run COJO to calculate conditional p-value, and found the toy example with the following command line:
# Select multiple associated SNPs through a stepwise selection procedure gcta64 --bfile test --chr 1 --maf 0.01 --cojo-file test.ma --cojo-slct --out test_chr1
The option
--bfile
specifies the genotype data which is in plink binary format to calculate LD matrix. I am wondering if I already have the LD matrix, can I use this matrix as the input of COJO. I noticed that SMR has the option--bld
which can read LD information from a binary file in BLD format. Besides, SMR can be used to make a BLD file from SNP genotype data. Does COJO have the same option? If so, can I get binary LD file from LD matrix instead of genotype data.Any insights are highly appreciated! Thank you!