ivis4ml / fssemr Goto Github PK

This concerns packages

Boom MCMCpack MasterBayes OpenMx ProFit Quartet RMariaDB RPostgres
RSQLite Rankcluster RcppQuantuccia Rlgt Rmalschains Ryacas StereoMorph
TDA bio3d bioacoustics bnclassify catSurv chngpt dpmixsim ecp episode
fssemR gof goftte hesim highlight jiebaR jmotif kernlab lidR multinet
oem phreeqc recurse rgl rlas robfilter sbart securitytxt spiderbar vennLasso

and almost all packages including headers from StanHeaders:

.../StanHeaders/include/stan/math/prim/mat/err/is_lower_triangular.hpp:25:27:
warning: 'ptr_fun<double, double>' is deprecated [-Wdeprecated-declarations]

clang/libc++ 9 has started to warn about these deprecated (in C++11)
functions, as seen in the CRAN results pages for fedora-clang.

Please take a look at your code and remove their usage at the next
update. C++11 is the default as from R 3.6.0, but if you want the
package to be usable with earlier versions and do not already do so,
specify C++11 or later (see 'Writing R Extensions').

--
Brian D. Ripley, [email protected]
Emeritus Professor of Applied Statistics, University of Oxford

Hi, i was trying to reproduce the data of the paper but i get stuck at the imputation step (which is the 3 step of the file "05_DataprocLungCancer.R"). I would appreciate if you could help me fix the issue that i found so that i can test the method and later use it with my data.

The specific part of the code is the following

###remove unchanged SNP and all Missing NA
###impute missing NA in SNP matrix
SNPvarmat = t(SNPvarmat)
SNPmap = SNPmap[colnames(SNPvarmat),c(2,3)]
colnames(SNPmap) = c("chr", "pos")
SNPmap[,2] = as.numeric(SNPmap[,2])
##dim(SNPvarmat) ## [1] 122 930002
PData2 = phenoData(gse2$eset) # SNP
SNPPheno = PData2@data[rownames(SNPvarmat), c(10, 11)]
SNPPheno[,1] = as.numeric(SNPPheno[,1])
SNPPheno[,2] = 2 - as.numeric(SNPPheno[,2])
colnames(SNPPheno) = c("Gender", "Status")
SNPData = create.gpData(pheno = SNPPheno, geno = SNPvarmat, map = SNPmap, map.unit = "bp") <-- PROBLEM HERE
SNPImputed = codeGeno(SNPData, impute=TRUE, impute.type="beagle", cores = 4) <-- CRASHES HERE
SNPvarmat = t(SNPImputed$geno)

I think the issue is that

SNPPheno[,1] = as.numeric(SNPPheno[,1])
SNPPheno[,2] = 2 - as.numeric(SNPPheno[,2])

are incorrect because SNPPheno have 2 columns that are the gender (which is only female) and the status (which is normal/tumor) are strings and the conversion as.numeric leads to R just filling the columns with NAs while i think synbreed wants the phenotype and not a data.frame with all NAs, as per create.gpData(pheno = SNPPheno,

The data to create SNPPheno are taken from the GEOdatabase file "GSE33356-GPL6801_series_matrix.txt.gz" just as it's already written on the code.
The values inside of SNPPheno after SNPPheno = PData2@data[rownames(SNPvarmat), c(10, 11)]

head(SNPPheno)
characteristics_ch1 characteristics_ch1.1
GSM824988 gender: female tissue: normal lung tissue
GSM824989 gender: female tissue: cancer lung tissue
GSM824990 gender: female tissue: normal lung tissue
GSM824991 gender: female tissue: cancer lung tissue
GSM824992 gender: female tissue: normal lung tissue
GSM824993 gender: female tissue: cancer lung tissue

So when i do

SNPPheno[,1] = as.numeric(SNPPheno[,1])
SNPPheno[,2] = 2 - as.numeric(SNPPheno[,2])

I get a warning message

SNPPheno[,1] = as.numeric(SNPPheno[,1])
Warning message:
NAs introduced by coercion
SNPPheno[,2] = 2 - as.numeric(SNPPheno[,2])
Warning message:
NAs introduced by coercion

head(SNPPheno)
characteristics_ch1 characteristics_ch1.1
GSM824988 NA NA
GSM824989 NA NA
GSM824990 NA NA
GSM824991 NA NA
GSM824992 NA NA
GSM824993 NA NA

I hope for a reply, thank you.