Is there a way to speed up the offTargetAnalysis() call by not trying to find out the restriction enzyme cut sites ?

• If Yes , then how ?

I have tried to enable parallelization by enable.multicore = TRUE, n.cores.max = 5. When I run my call I can see from the taskmanager that only 1 CPU is being used to 100%. Is there a way I can confirm that multiprocessing is happening for my offTargetAnalysis call?

My current call looks something like this

    res = offTargetAnalysis(inputFilePath = temp_gRNA, 
                        findgRNAs = FALSE, 
                        findgRNAsWithREcutOnly = FALSE, 
                        findPairedgRNAOnly = FALSE, 
                        chromToSearch = "chr1", 
                        outputDir = "/crisprseek_output_dir", 
                        overwrite = TRUE, 
                        gRNAoutputName = "temp_guide_rna_scores" , 
                        enable.multicore = TRUE, 
                        n.cores.max = 5, 
                        BSgenomeName = my_BSGenome_object, 
                        txdb = txdb,
                        scoring.method = "CFDscore",
                        outputUniqueREs = FALSE)

Thanks for the great questions, Durbar!

You can set findgRNAsWithREcutOnly = FALSE

For other scenarios, please refer to https://bioconductor.org/packages/release/bioc/vignettes/CRISPRseek/inst/doc/CRISPRseek.pdf.

The number of cores used depends on how many cores available in your computer. At most, it will use n.cores -1 in your computer. With your script, it should run pretty fast even without specifying enable.multicore. In addition, I noticed that you only specified chr1 in your script. Are you sure you only need to search for offtargets in chr1 only? To search for genome-wide offtargets, you will need to set chromToSearch = "all" which is the default.

If you need to run genome-wide gRNA design, I recommend use high performance computing cluster to run searches in parallel. For example, you can run offtarget search with one chromosome for each submitted job.

Best regards,

Julie

I have the same problem. Only one core is used although I have multicores enabled and set n.cores.max to 6. I have CRISPRseek version 1.30.1 installed. The machine has 8 cores and R version 4.0.5. Same is happening on a different machine with more cores.

This is my code:

    target.sequence = DNAStringSet(input$sequence)
    PAM.detail = c("NGG","NNG$|NGN$","3prime")
    paired.gRNA.info = c(FALSE)
    outpath = "/home/usr/tmp"

        out = offTargetAnalysis(inputFilePath = target.sequence,
                            gRNAoutputName = 'output',
                            findPairedgRNAOnly = paired.gRNA.info,
                            findgRNAs = TRUE,
                            BSgenomeName = my.BSgenome,
                            chromToSearch = 'all',
                            txdb = my.txdb,
                            outputDir = outpath,
                            overwrite = TRUE,
                            max.mismatch = 3,
                            orgAnn = my.org.db,
                            PAM = PAM.detail[1],
                            PAM.pattern = PAM.detail[2],
                            PAM.location = PAM.detail[3],
                            enable.multicore = TRUE,
                            n.cores.max=6)