Error in if (sum(!ind) != 0) { : missing value where TRUE/FALSE needed

[chuynh96]

After running: ZicoSeq.obj <- ZicoSeq(meta.dat = meta.dat3, feature.dat = comm2, grp.name = 'CancerStatus', feature.dat.type = "count",

Filter to remove rare taxa

                   prev.filter = 0.2, mean.abund.filter = 0,  
                   max.abund.filter = 0.002, min.prop = 0, 
                   # Winsorization to replace outliers
                   is.winsor = TRUE, outlier.pct = 0.03, winsor.end = 'top',
                   # Posterior sampling 
                   is.post.sample = TRUE, post.sample.no = 25, 
                   # Use the square-root transformation
                   link.func = list(function (x) x^0.5), stats.combine.func = max,
                   # Permutation-based multiple testing correction
                   perm.no = 99,  strata = NULL, 
                   # Reference-based multiple stage normalization
                   ref.pct = 0.5, stage.no = 6, excl.pct = 0.2,
                   # Family-wise error rate control
                   is.fwer = TRUE, verbose = TRUE, return.feature.dat = TRUE)

I am getting: NA features are filtered! Error in if (sum(!ind) != 0) { : missing value where TRUE/FALSE needed

How do I fix this?

[jchen1981]

Have you used the latest version in CRAN GUniFrac?JunSent from my iPhoneOn Nov 28, 2023, at 9:37 AM, chuynh96 @.***> wrote: After running: ZicoSeq.obj <- ZicoSeq(meta.dat = meta.dat3, feature.dat = comm2, grp.name = 'CancerStatus', feature.dat.type = "count",

Filter to remove rare taxa

prev.filter = 0.2, mean.abund.filter = 0, max.abund.filter = 0.002, min.prop = 0,

Winsorization to replace outliers

is.winsor = TRUE, outlier.pct = 0.03, winsor.end = 'top',

Posterior sampling

is.post.sample = TRUE, post.sample.no = 25,

Use the square-root transformation

link.func = list(function (x) x^0.5), stats.combine.func = max,

Permutation-based multiple testing correction

perm.no = 99, strata = NULL,

Reference-based multiple stage normalization

ref.pct = 0.5, stage.no = 6, excl.pct = 0.2,

Family-wise error rate control

is.fwer = TRUE, verbose = TRUE, return.feature.dat = TRUE) I am getting: NA features are filtered! Error in if (sum(!ind) != 0) { : missing value where TRUE/FALSE needed How do I fix this?

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[chuynh96]

Yes, I'm using version 1.8 of GUniFrac

[jchen1981]

It’s probably due to the data format issue. Make sure the data conform with the format specified in the doc.JunSent from my iPhoneOn Nov 28, 2023, at 9:55 AM, chuynh96 @.***> wrote: Yes, I'm using version 1.8 of GUniFrac

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[chuynh96]

I am analyzing many different datasets and the format is the same across the datasets, but it seems to work for some versus others. Is there something inherently wrong with the datasets that return the error above?

[jchen1981]

please send me the .Rdata to @. so I can reproduce your error first.Sent from my iPhoneOn Nov 28, 2023, at 10:04 AM, chuynh96 @.> wrote: I am analyzing many different datasets and the format is the same across the datasets, but it seems to work for some versus others. Is there something inherently wrong with the datasets that return the error above?

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[chuynh96]



On Nov 28, 2023, at 11:08 AM, Chen_LAB @.***> wrote:

please send me the .Rdata to @. so I can reproduce your error first.Sent from my iPhoneOn Nov 28, 2023, at 10:04 AM, chuynh96 @.> wrote: I am analyzing many different datasets and the format is the same across the datasets, but it seems to work for some versus others. Is there something inherently wrong with the datasets that return the error above?

—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you commented.Message ID: @.***> — Reply to this email directly, view it on GitHub https://github.com/jchen1981/ZicoSeq/issues/4#issuecomment-1830166780, or unsubscribe https://github.com/notifications/unsubscribe-auth/AWHF34TKPAQU7FYMOKYH22DYGYD6VAVCNFSM6AAAAAA7567RQ6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQMZQGE3DMNZYGA. You are receiving this because you authored the thread.

[sophieleech]

Was there a solution to this? I am getting the same issue - has worked previously but is now not working for one particular dataset despite the same format

[sophieleech]

In case anyone else comes across this - in my case the issue was caused by a couple samples where all taxa = 0