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Hello,

I am trying to use CNAclinic for CNV calling in a cfDNA WGS data with high coverage around 100x which leads to a ~200 GBs bam file. However, running CNAclinic at the first step when using the processForSegmentation() function face error due to the memory allocation on the cluster which can not be solved even by allocating 200 GB of memory.
I noticed this error can be solved by chunkSize in QDNAseq tool. So, I wonder if there is any option like that in CNAclinic to optimize the bin segmentation process?
Thanks in advance.

The error i got:
IH01-simulated-s1_sorted (1 of 1): extracting reads ...Error in value[3L] :
'R_Realloc' could not re-allocate memory (18446744065128005632 bytes)
file: /work/FAC/FBM/DBC/cdessim2/default/fpalizba/cfDNA-CNV/validation/IH01-simulated/IH01-simulated-s1_sorted.bam
index: NA
Calls: processForSegmentation ... tryCatch -> tryCatchList -> tryCatchOne ->
Execution halted

Hi,

I am getting the following error with runSegmentation on R v4.0.2:
The following error occured in HMMcopy::HMMsegment() Error: RangedData objects are defunct. Please migrate your code to use GRanges or GRangesList objects instead. See IMPORTANT NOTE in ?RangedData

The HMM algorithm will be skipped
Error in runSegmentation(processedData, genome = "hg19") : HMMcopy segmentation did not return the expected number of bins or samples

Will there be an update to resolve the defunct objects?

Thanks,
Paul

.reorderbyChrom function in runSegmentation results in " In xtfrm.data.frame(x) : cannot xtfrm data frames" error due to original code ( x <- x[order(x["chromosome"], x["start"]), ] ) being unable to successfully arrange chromosomes in ascending order.

Please consider updating to: x <- dplyr::arrange(x,chromosome)

Hi, i'm trying to run the example of segmentation in R version 4.1.3:

data(exData)

exData <- exData[exData$chromosome == "1", ]

CNAData <- runSegmentation(exData, genome="hg19",
                           segmentType=c("CBS", "PLS", "HMM"),
                           segmentsToSummarise=c("CBS", "PLS", "HMM"),
                           summaryMethod="mean")

But i get the following error:

Running HMMcopy segmentation
P16_SF_Bx

The following error occured in HMMcopy::HMMsegment()
Error: 'RangedData' is not an exported object from 'namespace:IRanges'

The HMM algorithm will be skipped
Error in runSegmentation(exData, genome = "hg19", segmentType = c("CBS",  :

HMMcopy segmentation did not return the expected
    number of bins or samples
In addition: Warning messages:
1: In xtfrm.data.frame(x) : cannot xtfrm data frames
2: In xtfrm.data.frame(x) : cannot xtfrm data frames

The same error happens when running with the output of processForSegmentation

Thank you very much

Hello,

I'd like to run my data on hg38 through your really cool-looking pipeline; however I only see hg19 mentioned in processforSegmentations. Is it possible to use data from hg38?
Thanks

Hi,
I am running the function optimalBinsize on a bunch of shallow WGS .bam files in R version 4.2.1

When the last sample is processed by the function, I get the following error:

Error in if (class(medianReadsPerBin) == "numeric") { : the condition has length > 1

The problem is that when multiple bam files are processed class(medianReadsPerBin) outputs "matrix" "array" causing the condition to have length > 1.

Best

I was wondering if this very great pipeline of analysis can be also adapted on Whole Exome Sequencing data, did you already performed any test?

Thank you!