Hi every one
During microarray meta-analysis, I encounter below error, (“anals” class is a list).
> es_res <- es_meta(anals, by_source = TRUE)
Error in quantile.default(x, probs = c(0.25, 0.75)) :
missing values and NaN's not allowed if 'na.rm' is FALSE
please guide me, which one is more logical, remove NaN or replace with a value?
How to remove or replace NaN with a value?
I would be very pleased if you could guide me.
What is inside each element of the anals list? A number a complex object or other things...
Hi Lluís,
I'm sorry for the delay in replying,
the lists include matrix, table, and character.
And are you sure you can use es_meta on that list? From which package is this function? Have you checked if in any of these objects there are some NA values?
Name of the package is “crossmeta”. As shown in the error, “anals” contains missing value (Na), I remove NA with
anals<-
na
.omit(
anals
)
, but I encountered an error in removing NaNs.The error is occuring inside
fdrtool::fdrtool
but I don't know why. If you can share a reproducible example I'll track it down.Hi Dr pickering,
Thanks for your attention,
library(crossmeta)
library(shiny)
gse_names <- c("GSE87105", "GSE87108")
get_raw(gse_names)
esets <- load_raw(gse_names)
# I select young samples as control and old samples as case, In both GSE number.
anals <- diff_expr(esets)
es_res <- es_meta(anals, by_source = TRUE)
Error in quantile.default(x, probs = c(0.25, 0.75)) :
missing values and NaN's not allowed if 'na.rm' is FALSE
Hi Morteza,
I wasn't able to reproduce the error so I'm guessing it is a bug that has been fixed. Please download the latest version from github and try again. You should be able to do this with
devtools::install_github('alexvpickering/crossmeta')
orremotes::install_github('alexvpickering/crossmeta').
Let me know if that doesn't work.Hi Dr pickering,
Thank you so much, your answer was reasonable and accurate.
After downloading the latest version of github, the previous error has been resolved.
But I had to change TRUE to FALSE (in below command) to analyze done.
es_res <- es_meta(anals, by_source = FALSE)
while source = TRUE, The following message was given.
es_res <- es_meta(anals, by_source = TRUE)
Sources missing from diff_exprs (to add, use add_sources).
Continuing with by_source = FALSE.
However, the result of the analysis is valid?
Hi Morteza,
Yes, the analysis is still valid. The difference is that all contrasts are used to perform a single meta-analysis. If sources are added, then separate meta-analyses are performed for contrasts belonging to each source as well as for all contrasts. This would be useful if you want to do a separate meta-analyses for contrasts from e.g. liver and brain. To specify sources in a GUI, run:
Dear Dr Pickering,
Thank you so much for your valuable guidance.