xinhe-lab / mapgen Goto Github PK

Hi Dr.Luo
We encountered an error when using the [hg19] ukb_b37_0.1_chr8.R_snp.3392926_3783017.RDS and ukb_b37_0.1_chr8.R_snp.3392926_3783017.Rvar with the code below. All files are running well except for this region.Could you provide advice on how to resolve this issue? Thank you in advance!

library(data.table)
library(mapgen)
locus<-848
LD_blocks <- readRDS(system.file('extdata', 'LD.blocks.EUR.hg19.rds', package='mapgen'))
####locus 848 <- 
###chr | start | end | locus
##8 | 3392926 | 3783017 | 848
LDREF <- load_UKBB_LDREF(LD_blocks, 
                         locus = locus, 
                         LDREF.dir = "D:/fine_mapping", 
                         prefix = "ukb_b37_0.1")

Huang

Hi Dr.Luo

When we using the reference panel generated from UK10K with the GWAS summary dataset, we encountered a problem during the run_finemapping step. However, the reference panel from 1000G performed well with this GWAS dataset. The error report is listed below. Could you provide advice on how to resolve this issue? Thank you in advance!

Huang

> susie.res <- run_finemapping(sumstats = gwas.sumstats, 
+                              bigSNP = bigSNP, 
+                              priortype = 'uniform', 
+                              n = 24009,
+                              L = 1)
Finemapping locus 1...
Run susie_rss...
WARNING: XtX is not symmetric; forcing XtX to be symmetric by replacing XtX with (XtX + t(XtX))/2
Error in susie_suff_stat(XtX = XtX, Xty = Xty, n = n, yty = (n - 1) *  : 
  Input XtX matrix contains NAs

Hi Dr.Luo

Our work requires the LD matrix for the EAS and AFR populations. Do you have plans to provide the LD matrix for other populations, or should we calculate the LD matrix ourselves? If so, would you be willing to provide the workflow for creating the LD matrix file using the bed, bim, and fam files?

Best,
Huang

Hi, sorry to disturb you. I intend to install mapgen, but received this error:

Error: Failed to install 'mapgen' from GitHub:
no lines available in input

Could you please help me solve this problem? Thanks a lot.

Dear Sir or Madam,

Thank you for your excellent work. We encountered an issue while running the gene mapping module using the GWAS tool. Even with the default settings in MapGen, we noticed that some of the identified genes have large posterior inclusion probability (PIP >1). Is this a common result? Below is the header of our output file We appreciate your response in advance.

  top_gene top_locus_gene_pip top_gene_pip
1 ARHGEF16              0.677        0.689
2 C1orf174              1.426        1.428
3    AJAP1              3.015        3.574
4   CAMTA1              1.321        1.366
5  SLC45A1              1.159        1.159
6 SLC25A33              0.097        0.106

Yu-Feng Huang