Error when using coloc.signals

[nbbarrientos]

Hello,

First, I wanted to thank you for this great tool. Second, I wanted to run coloc.signals but I am encountering what seems to be a memory error and some warnings regarding sdY.est (even when I provide varbeta, MAF, and N):

Error: vector memory exhausted (limit reached?) In addition: Warning messages: 1: In sdY.est(vbeta = varbeta, maf = MAF, n = N) : estimating sdY from maf and varbeta, please directly supply sdY if known 2: In sdY.est(d$varbeta, d$MAF, d$N) : estimating sdY from maf and varbeta, please directly supply sdY if known

I have tried running it locally on Rstudio and also on a cluster and no matter how much memory I provide, it still fails. I know coloc.signals is part of the new coloc-4.0-4 version so I was wondering if this might be a bug. Thank you for your help.

Nelson Barrientos

[chr1swallace]

Hi Nelson,

it would help me understand how this arose if you show me how you called coloc, and the output of summary() run on each object you pass. Is that possible?

C

On Wed, 2021-01-20 at 05:55 -0800, nbbarrientos wrote:

Hello,

First, I wanted to thank you for this great tool. Second, I wanted to run coloc.signals but I am encountering what seems to be a memory error and some warnings regarding sdY.est (even when I provide varbeta, MAF, and N):

Error: vector memory exhausted (limit reached?) In addition: Warning messages: 1: In sdY.est(vbeta = varbeta, maf = MAF, n = N) : estimating sdY from maf and varbeta, please directly supply sdY if known 2: In sdY.est(d$varbeta, d$MAF, d$N) : estimating sdY from maf and varbeta, please directly supply sdY if known

I have tried running it locally on Rstudio and also on a cluster and no matter how much memory I provide, it still fails. I know coloc.signals is part of the new coloc-4.0-4 version so I was wondering if this might be a bug. Thank you for your help.

Nelson Barrientos

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[nbbarrientos]

Hi Chris,

Thank you for your response. This is how I called coloc:

p = coloc.signals( dataset1 = list(pvalues = y$p, snp = y$SNP, N = 296525, type = "cc", s = 0.12, MAF = y$freq, beta = y$b, varbeta = y$varbeta), dataset2 = list(pvalues = x$pval, snp = x$SNP, type = "quant", MAF = x$MAF, N = 149, beta = x$b, varbeta = x$varbeta), method = c("single"), mode = c("iterative"), p1 = 1e-04, p2 = 1e-04, p12= 1e-05, maxhits = 3)

I'm unable to provide the output from summary() because I think it fails before it gets there. I was also wondering if an alternative would be to run coloc.abf since I'm using method = c("single")?

Thank you

[chr1swallace]

I mean, can you show me summary(y) summary(x) please?

On Wed, 2021-01-20 at 13:23 -0800, nbbarrientos wrote:

Hi Chris,

Thank you for your response. This is how I called coloc:

p = coloc.signals( dataset1 = list(pvalues = y$p, snp = y$SNP, N = 296525, type = "cc", s = 0.12, MAF = y$freq, beta = y$b, varbeta = y$varbeta), dataset2 = list(pvalues = x$pval, snp = x$SNP, type = "quant", MAF = x$MAF, N = 149, beta = x$b, varbeta = x$varbeta), method = c("single"), mode = c("iterative"), p1 = 1e-04, p2 = 1e-04, p12= 1e-05, maxhits = 3)

I'm unable to provide the output from summary() because I think it fails before it gets there. I was also wondering if an alternative would be to run coloc.abf since I'm using method = c("single")?

Thank you

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[nbbarrientos]

Oh, my bad. These are the summaries for both:

summary(x)

summary(y)

[chr1swallace]

I suspect R is getting upset when it tries to fit a regression to 8 million observations to estimate the variance of your quantitative trait. It seems you are supplying the full GWAS summary statistics to coloc. It is not designed for that, but for investigating whether two traits share a causal variant in a small LD defined region. How small? I find with dense genotyping they are typically from 1000-10000 SNPs. See the FAQ https://github.com/chr1swallace/coloc/blob/master/FAQ.md#can-the-process-of-identifying-colocalized-variants-be-carried-out-genome-wide-or-is-it-meant-to-be-done-in-defined-small-regions

On Thu, 2021-01-21 at 05:38 -0800, nbbarrientos wrote:

Oh, my bad. These are the summaries for both:

summary(x)

summary(y)

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[nbbarrientos]

Interesting, I think I have an idea to address this issue. I'll give it a try by breaking the analysis into smaller pieces. Thank you very much for your help

Nelson