Hi, I am running a script where I want to get sexes of the samples using getsex. When i load the data file i can clearly see there are male and female samples in it. Also everything goes perfectly until it reaches getsex function and i get caught segfault address 0x1, cause 'memory not mapped' along with traceback options which i am sure problem lies with getsex function. Can some one help me identify what could be the reason. Computing power is maximum 40 G still throws the error so memory is not the issue.

Code should be placed in three backticks as shown below

#loading the sample sheet
load(paste0(path, "sample_sheets/sample_sheet_fit.RData"))
print(ss_t)
dim(ss_t) 

file.exists(paste0(dpath,ss_t$fileloc,"_Grn.idat")) %>% all %>% stopifnot
file.exists(paste0(dpath,ss_t$fileloc,"_Red.idat")) %>% all %>% stopifnot
num_samps <- 100
num_its   <- ceiling(nrow(ss_t) / num_samps)

qcres <- lapply(1:num_its, function(i) {

    low_ind <- (i-1)*num_samps + 1
    hgh_ind <- min(nrow(ss_t), i*num_samps)

print(i)    #zu
print(c(low_ind, hgh_ind)) #zu

#reading in the data from idat files
print ("Reading .idat files")
RGset <- read.metharray(paste0(dpath,ss_t$fileloc[low_ind:hgh_ind]), verbose = TRUE)

#processing - RGset_raw contains only methylated and unmethylated signals.
print("Getting methylated and unmethylated signals")
RGset_raw <- preprocessRaw(RGset)
print(RGset_raw)
#predicting sex
pred_sex <- getSex(mapToGenome(ratioConvert(RGset_raw, what = "both", keepCN = TRUE)))
psex <- as.data.frame(pred_sex)

#quality control function
qc <- getQC(RGset_raw)
head(qc)

return(list(psex = psex, qc = qc))
})

predsex <- map(qcres, "psex") %>% 
             do.call(rbind,.) %>% 
             select(-predictedSex) #determining predicted elsewhere

dim(predsex) #[1] 600   3
predsex$sentrix_id <- rownames(predsex)

qcint   <- map(qcres,"qc") %>% do.call(rbind,.) %>% as.data.frame(stringsAsFactors=F)
dim(qcint) #[1] 600   2
qcint$sentrix_id <- rownames(qcint)

setequal(qcint$sentrix_id, predsex$sentrix_id) %>% stopifnot
(!any(duplicated(qcint$sentrix_id)))           %>% stopifnot
(!any(is.na(qcint$sentrix_id)))                %>% stopifnot

# final data frame
qcres <- inner_join(qcint, predsex) %>% 
           mutate(yx_diff = yMed - xMed, med_intensity = (mMed + uMed)/2)

save(qcres, file = paste0(opath,"qc_results.RData"))



# OUTPUT  
*** caught segfault ***
address 0x1, cause 'memory not mapped'

Traceback:
 1: colMedians(CN, rows = xIndex, na.rm = TRUE)
 2: colMedians(CN, rows = xIndex, na.rm = TRUE)
 3: .getSex(CN = CN, xIndex = xIndex, yIndex = yIndex, cutoff = cutoff)
 4: getSex(mapToGenome(ratioConvert(RGset_raw, what = "both", keepCN = TRUE)))
 5: FUN(X[[i]], ...)
 6: lapply(1:num_its, function(i) {    low_ind <- (i - 1) * num_samps + 1    hgh_ind <- min(nrow(ss_t), i * num_samps)    print(i)    print(c(low_ind, hgh_ind))    print("Reading .idat files")    RGset <- read.metharray(paste0(dpath, ss_t$fileloc[low_ind:hgh_ind]),         verbose = TRUE)    print("Getting methylated and unmethylated signals")    RGset_raw <- preprocessRaw(RGset)    print(RGset_raw)    pred_sex <- getSex(mapToGenome(ratioConvert(RGset_raw, what = "both",         keepCN = TRUE)))    psex <- as.data.frame(pred_sex)    qc <- getQC(RGset_raw)    head(qc)    return(list(psex = psex, qc = qc))})
 7: lapply(1:num_its, function(i) {    low_ind <- (i - 1) * num_samps + 1    hgh_ind <- min(nrow(ss_t), i * num_samps)    print(i)    print(c(low_ind, hgh_ind))    print("Reading .idat files")    RGset <- read.metharray(paste0(dpath, ss_t$fileloc[low_ind:hgh_ind]),         verbose = TRUE)    print("Getting methylated and unmethylated signals")    RGset_raw <- preprocessRaw(RGset)    print(RGset_raw)    pred_sex <- getSex(mapToGenome(ratioConvert(RGset_raw, what = "both",         keepCN = TRUE)))    psex <- as.data.frame(pred_sex)    qc <- getQC(RGset_raw)    head(qc)    return(list(psex = psex, qc = qc))})