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bardetlab / methylasso

A segmentation approach to analyze DNA methylation patterns and identify differentially methylation regions from whole-genome datasets
MIT License
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Program doesn't run in conda #4

Closed desmodus1984 closed 1 month ago

desmodus1984 commented 7 months ago

Hi,

I installed the program using the conda instructions and when I tried running the code, after activating the environment it doesn't work.

nohup Rscript /home/juaguila/appz/methylasso-main/MethyLasso.R --n1 HIGH --c1 V00001.deduplicated.bismark.cov.gz,V00750.deduplicated.bismark.cov.gz,V00796.deduplicated.bismark.cov.gz --n2 LOW --c2 V00294.deduplicated.bismark.cov.gz,V00296.deduplicated.bismark.cov.gz,V00297.deduplicated.bismark.cov.gz -c 10 --meth 5 -q 0.05 -o test-low-high -t 10

I got the error "Fatal error: cannot open file 'MethyLasso.R': No such file or directory". Then I tried coping the file, and I got this error: "Error in library(R.utils) : there is no package called ‘R.utils’ Calls: suppressPackageStartupMessages -> withCallingHandlers -> library Execution halted"

delbala commented 7 months ago

Hi,

I modified the conda conda_env.yml script to install the R.Utils package. It should work now.

Additionally, there is an error in your code. If you add the --meth option, you must also include the --cov option, as indicated in the README in Section 4 - Input Format.

If you don't specify an input format, it will by default take the bismark input format: chr / start / end / percent_methylation / count_methylated / count_unmethylated. Alternatively, if you provide an input format different from bismark, you must specify the column numbers where the methylated AND unmethylated C's are located (--mC and --uC ) OR you only specify the coverage AND methylation percentage columns (--cov and --meth)

I hope I was able to help you. Delphine

desmodus1984 commented 7 months ago

Good morning Delphine,

Should I reinstall methylasso or can I just update it in conda?

Thank you very much.

Juan Pablo Aguilar

From: Delphine Balaramane @.> Sent: Thursday, March 28, 2024 9:14:21 AM To: abardet/methylasso @.> Cc: Aguilar Cabezas, Juan Pablo @.>; Author @.> Subject: [External] Re: [abardet/methylasso] Program doesn't run in conda (Issue #4)

Use caution with links and attachments.

Hi,

I modified the conda conda_env.yml script to install the R.Utils package. It should work now.

Additionally, there is an error in your code. If you add the --meth option, you must also include the --cov option, as indicated in the README in Section 4 - Input Format.

If you don't specify an input format, it will by default take the bismark input format: chr / start / end / percent_methylation / count_methylated / count_unmethylated. Alternatively, if you provide an input format different from bismark, you must specify the column numbers where the methylated AND unmethylated C's are located (--mC and --uC ) OR you only specify the coverage AND methylation percentage columns (--cov and --meth)

I hope I was able to help you. Delphine

— Reply to this email directly, view it on GitHubhttps://github.com/abardet/methylasso/issues/4#issuecomment-2025158389, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AJWD2VPVI43K6KNUIZQHSSDY2QCR3AVCNFSM6AAAAABFGCNZ32VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRVGE2TQMZYHE. You are receiving this because you authored the thread.Message ID: @.***>

delbala commented 7 months ago

Hi,

You need to re-download the methylasso package from github to get the new version and install it again.

Best, Delphine

desmodus1984 commented 7 months ago

Hi, I created another environment and installed all the required packages and methylasso. I tried running it two times and it failed.

The first attempt, I used the bismark files, with the following code

nohup Rscript /home/juaguila/appz/methylasso-main/MethyLasso.R --n1 HIGH --c1 V00001.deduplicated.bismark.cov.gz,V00750.deduplicated.bismark.cov.gz,V00796.deduplicated.bismark.cov.gz --n2 LOW --c2 V00294.deduplicated.bismark.cov.gz,V00296.deduplicated.bismark.cov.gz, V00297_methyldackel_CpG.bedGraph -c 10 -q 0.05 -o test-low-high -t 20 > methylasso1.log

It ran well for a while and then failed.

Reading condition HIGH with 3 replicate(s) in memory.. Reading condition LOW with 3 replicate(s) in memory..

Part 1: Beginning analysis of the levels of DNA methylation in a single condition

Step 1: Fit of methylation signal

Processing chromosome: NW_022882922.1 Processing chromosome: NW_022882923.1 Processing chromosome: NW_022882924.1 Processing chromosome: NW_022882925.1 Processing chromosome: NW_022882926.1 Processing chromosome: NW_022882927.1 Processing chromosome: NW_022882928.1 Processing chromosome: NW_022882929.1 Processing chromosome: NW_022882930.1 Processing chromosome: NW_022882931.1 Processing chromosome: NW_022882949.1 Processing chromosome: NW_022882932.1 Processing chromosome: NW_022882933.1 Processing chromosome: NW_022882935.1 Processing chromosome: NW_022882934.1 Processing chromosome: NW_022882953.1 Processing chromosome: NW_022882948.1 Processing chromosome: NW_022882936.1 Processing chromosome: NW_022882952.1 Processing chromosome: NW_022882974.1 Processing chromosome: NW_022882954.1 Processing chromosome: NW_022882957.1 Processing chromosome: NW_022882937.1 Processing chromosome: NW_022882942.1 Processing chromosome: NW_022882971.1 Processing chromosome: NW_022882994.1 Processing chromosome: NW_022882991.1 Processing chromosome: NW_022882938.1 Processing chromosome: NW_022882955.1 Processing chromosome: NW_022883013.1 Processing chromosome: NW_022883033.1 Processing chromosome: NW_022882958.1 Processing chromosome: NW_022883053.1 Processing chromosome: NW_022882939.1 Processing chromosome: NW_022883073.1 Processing chromosome: NW_022882978.1 Processing chromosome: NW_022883096.1 Processing chromosome: NW_022882977.1 Processing chromosome: NW_022882970.1 Processing chromosome: NW_022882998.1 Processing chromosome: NW_022883116.1 Processing chromosome: NW_022882990.1 Processing chromosome: NW_022883136.1 Processing chromosome: NW_022883156.1 Processing chromosome: NW_022883176.1 Processing chromosome: NW_022883020.1 Processing chromosome: NW_022882940.1 Processing chromosome: NW_022883197.1 Processing chromosome: NW_022883217.1 Processing chromosome: NW_022883238.1 Processing chromosome: NW_022883258.1 Processing chromosome: NW_022883278.1 Processing chromosome: NW_022883016.1 Processing chromosome: NW_022882941.1 Processing chromosome: NW_022883298.1 Processing chromosome: NW_022883036.1 Processing chromosome: NW_022883319.1 Processing chromosome: NW_022882961.1 Processing chromosome: NW_022883339.1 Processing chromosome: NW_022883361.1 Processing chromosome: NW_022883381.1 Processing chromosome: NW_022883040.1 Processing chromosome: NW_022883060.1 Processing chromosome: NW_022883402.1 Processing chromosome: NW_022883080.1 Processing chromosome: NW_022882951.1 Processing chromosome: NW_022883423.1 Processing chromosome: NW_022883103.1 Processing chromosome: NW_022883443.1 Processing chromosome: NW_022883123.1 Processing chromosome: NW_022883464.1 Processing chromosome: NW_022883143.1 Processing chromosome: NW_022883012.1 Processing chromosome: NW_022882960.1 Processing chromosome: NW_022883163.1 Processing chromosome: NW_022883056.1 Processing chromosome: NW_022882962.1 Processing chromosome: NW_022883484.1 Processing chromosome: NW_022883184.1 Processing chromosome: NW_022883504.1 Processing chromosome: NW_022883204.1 Processing chromosome: NW_022882946.1 Processing chromosome: NW_022883524.1 Processing chromosome: NW_022883224.1 Processing chromosome: NW_022883546.1 Processing chromosome: NW_022883245.1 Processing chromosome:Processing chromosome: NW_022883568.1NW_022883265.1

Processing chromosome: NW_022883589.1 Processing chromosome: NW_022883285.1 Processing chromosome: NW_022883609.1 Processing chromosome: NW_022883305.1 Processing chromosome: NW_022882982.1 Processing chromosome: NW_022883076.1 Processing chromosome: NW_022883629.1 Processing chromosome: NW_022883032.1 Processing chromosome: NW_022883002.1 Processing chromosome: NW_022883099.1 Processing chromosome: NW_022883649.1 Processing chromosome: Processing chromosome:NW_022883024.1 NW_022883670.1

and I got the following error:

Processing chromosome: NW_022884269.1 Processing chromosome: NW_022884289.1 Processing chromosome: NW_022884311.1 Processing chromosome: NW_022884332.1 Processing chromosome: NW_022883091.1 Processing chromosome: NW_022883919.1 Processing chromosome: NW_022884350.1 Processing chromosome: NW_022883890.1 Processing chromosome: NW_022884298.1

Warning: the following chromosomes did not work: NW_022882943.1 NW_022882952.1 NW_022882973.1 NW_022883011.1 NW_022883040.1 NW_022883065.1 NW_022883072.1 NW_022883073.1 NW_022883097.1 NW_022883171.1 NW_022883173.1 NW_022883199.1 NW_022883203.1 NW_022883215.1 NW_022883240.1 NW_022883247.1 NW_022883249.1 NW_022883311.1 NW_022883323.1 NW_022883358.1 NW_022883373.1 NW_022883401.1 NW_022883404.1 NW_022883444.1 NW_022883450.1 NW_022883458.1 NW_022883465.1 NW_022883496.1 NW_022883513.1 NW_022883515.1 NW_022883537.1 NW_022883540.1 NW_022883552.1 NW_022883579.1 NW_022883592.1 NW_022883615.1 NW_022883616.1 NW_022883642.1 NW_022883667.1 NW_022883676.1 NW_022883688.1 NW_022883743.1 NW_022883758.1 NW_022883770.1 NW_022883775.1 NW_022883780.1 NW_022883782.1 NW_022883796.1 NW_022883815.1 NW_022883844.1 NW_022883846.1 NW_022883855.1 NW_022883859.1 NW_022883896.1 NW_022883953.1 NW_022883959.1 NW_022883969.1 NW_022883975.1 NW_022884003.1 NW_022884028.1 NW_022884062.1 NW_022884068.1 NW_022884071.1 NW_022884082.1 NW_022884096.1 NW_022884106.1 NW_022884110.1 NW_022884116.1 NW_022884119.1 NW_022884131.1 NW_022884176.1 NW_022884181.1 NW_022884196.1 NW_022884203.1 NW_022884216.1 NW_022884222.1 NW_022884327.1 NW_022884349.1 NW_022882956.1 NW_022883091.1 NW_022883179.1 NW_022883236.1 NW_022883315.1 NW_022883357.1 NW_022883391.1 NW_022883449.1 NW_022883528.1 NW_022883543.1 NW_022883561.1 NW_022883562.1 NW_022883581.1 NW_022883656.1 NW_022883690.1 NW_022883694.1 NW_022883726.1 NW_022883749.1 NW_022883865.1 NW_022883890.1 NW_022883895.1 NW_022883919.1 NW_022883944.1 NW_022883973.1 NW_022883978.1 NW_022884002.1 NW_022884066.1 NW_022884114.1 NW_022884155.1 NW_022884169.1 NW_022884177.1 NW_022884213.1 NW_022884214.1 NW_022884302.1 NW_022884329.1 NW_022883954.1 NW_022884144.1 NW_022882967.1 NW_022883090.1 NW_022884298.1 NW_022883791.1 Step 2: Segmentation and identification of PMDs, LMRs, UMRs and DMVs

caught segfault address (nil), cause 'memory not mapped'

Traceback: 1: .External(list(name = "InternalFunction_invoke", address = <pointer: 0x55c2be4960c0>, dll = list(name = "Rcpp", path = "/home/juaguila/.conda/envs/methylasso/lib/R/library/Rcpp/libs/Rcpp.so", dynamicLookup = TRUE, handle = <pointer: 0x55c2c1116b50>, info = <pointer: 0x55c2b986dca0>), numParameters = -1L), <pointer: 0x55c2b936d4c0>, data, tol_val) 2: MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val) 3: as.data.table(MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val)) 4: MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) 5: eval(c.expr, envir = args, enclos = envir) 6: eval(c.expr, envir = args, enclos = envir) 7: doTryCatch(return(expr), name, parentenv, handler) 8: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 9: tryCatchList(expr, classes, parentenv, handlers) 10: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 11: FUN(X[[i]], ...) 12: lapply(X = S, FUN = FUN, ...) 13: doTryCatch(return(expr), name, parentenv, handler) 14: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 15: tryCatchList(expr, classes, parentenv, handlers) 16: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 17: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 18: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 19: FUN(X[[i]], ...) 20: lapply(seq_len(cores), inner.do) 21: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 22: e$fun(obj, substitute(ex), parent.frame(), e$data) 23: foreach(ch = data[, unique(chr)], .combine = function(x, y) { list(lmr_umr_valley = rbind(x$lmr_umr_valley, y$lmr_umr_valley), pmd = rbind(x$pmd, y$pmd), ov = rbind(x$ov, y$ov))}) %dopar% { mdata = data[chr == ch] mret = list(estimates = ret$estimates[ret$estimates$chr == ch, ], detection.type = ret$detection.type, ref.cond = ret$ref.cond) segments = MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) segments$lmr_umr_valley[, :=(chr, ch)] segments$pmd[, :=(chr, ch)] segments$ov[, :=(chr, ch)] segments} 24: MethyLasso:::segment_methylation(data, ret, ncores = t, pmd_max_beta = m, min_num_cpgs = n) An irrecoverable exception occurred. R is aborting now ...

caught segfault address (nil), cause 'memory not mapped'

Traceback: 1: .External(list(name = "InternalFunction_invoke", address = <pointer: 0x55c2be4960c0>, dll = list(name = "Rcpp", path = "/home/juaguila/.conda/envs/methylasso/lib/R/library/Rcpp/libs/Rcpp.so", dynamicLookup = TRUE, handle = <pointer: 0x55c2c1116b50>, info = <pointer: 0x55c2b986dca0>), numParameters = -1L), <pointer: 0x55c2b936d4c0>, data, tol_val) 2: MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val) 3: as.data.table(MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val)) 4: MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) 5: eval(c.expr, envir = args, enclos = envir) 6: eval(c.expr, envir = args, enclos = envir) 7: doTryCatch(return(expr), name, parentenv, handler) 8: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 9: tryCatchList(expr, classes, parentenv, handlers) 10: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 11: FUN(X[[i]], ...) 12: lapply(X = S, FUN = FUN, ...) 13: doTryCatch(return(expr), name, parentenv, handler) 14: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 15: tryCatchList(expr, classes, parentenv, handlers) 16: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 17: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 18: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 19: FUN(X[[i]], ...) 20: lapply(seq_len(cores), inner.do) 21: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 22: e$fun(obj, substitute(ex), parent.frame(), e$data) 23: foreach(ch = data[, unique(chr)], .combine = function(x, y) { list(lmr_umr_valley = rbind(x$lmr_umr_valley, y$lmr_umr_valley), pmd = rbind(x$pmd, y$pmd), ov = rbind(x$ov, y$ov))}) %dopar% { mdata = data[chr == ch] mret = list(estimates = ret$estimates[ret$estimates$chr == ch, ], detection.type = ret$detection.type, ref.cond = ret$ref.cond) segments = MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) segments$lmr_umr_valley[, :=(chr, ch)] segments$pmd[, :=(chr, ch)] segments$ov[, :=(chr, ch)] segments} 24: MethyLasso:::segment_methylation(data, ret, ncores = t, pmd_max_beta = m, min_num_cpgs = n) An irrecoverable exception occurred. R is aborting now ...

caught segfault address (nil), cause 'memory not mapped'

Traceback: 1: .External(list(name = "InternalFunction_invoke", address = <pointer: 0x55c2be4960c0>, dll = list(name = "Rcpp", path = "/home/juaguila/.conda/envs/methylasso/lib/R/library/Rcpp/libs/Rcpp.so", dynamicLookup = TRUE, handle = <pointer: 0x55c2c1116b50>, info = <pointer: 0x55c2b986dca0>), numParameters = -1L), <pointer: 0x55c2b936d4c0>, data, tol_val) 2: MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val) 3: as.data.table(MethyLasso:::segment_methylation_helper(sig.df, tol_val = tol_val)) 4: MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) 5: eval(c.expr, envir = args, enclos = envir) 6: eval(c.expr, envir = args, enclos = envir) 7: doTryCatch(return(expr), name, parentenv, handler) 8: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 9: tryCatchList(expr, classes, parentenv, handlers) 10: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 11: FUN(X[[i]], ...) 12: lapply(X = S, FUN = FUN, ...) 13: doTryCatch(return(expr), name, parentenv, handler) 14: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 15: tryCatchList(expr, classes, parentenv, handlers) 16: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 17: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 18: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 19: FUN(X[[i]], ...) 20: lapply(seq_len(cores), inner.do) 21: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 22: e$fun(obj, substitute(ex), parent.frame(), e$data) 23: foreach(ch = data[, unique(chr)], .combine = function(x, y) { list(lmr_umr_valley = rbind(x$lmr_umr_valley, y$lmr_umr_valley), pmd = rbind(x$pmd, y$pmd), ov = rbind(x$ov, y$ov))}) %dopar% { mdata = data[chr == ch] mret = list(estimates = ret$estimates[ret$estimates$chr == ch, ], detection.type = ret$detection.type, ref.cond = ret$ref.cond) segments = MethyLasso:::segment_methylation_singlechr(mdata, mret, ...) segments$lmr_umr_valley[, :=(chr, ch)] segments$pmd[, :=(chr, ch)] segments$ov[, :=(chr, ch)] segments} 24: MethyLasso:::segment_methylation(data, ret, ncores = t, pmd_max_beta = m, min_num_cpgs = n) An irrecoverable exception occurred. R is aborting now ...

caught segfault address (nil), cause 'memory not mapped'

Then, I tried running the bedgraph files generated with methyldackel, which have the same input format, though I had to eliminate the first line which is weird:

and I used the following code to eliminate the first line for i in *_methyldackel_CpG.bedGraph do base=$(basename $i "_R1_val_1.fq.gz") tail -n +2 ${base}_methyldackel_CpG.bedGraph > ${base}_CpG.bedGraph

done

and then, this to run methylasso nohup Rscript /home/juaguila/appz/methylasso-main/MethyLasso.R --n1 HIGH --c1 V00001_methyldackel_CpG.bedGraph_CpG.bedGraph,V00750_methyldackel_CpG.bedGraph_CpG.bedGraph,V00796_methyldackel_CpG.bedGraph_CpG.bedGraph --n2 LOW --c2 V00294_methyldackel_CpG.bedGraph_CpG.bedGraph,V00296_methyldackel_CpG.bedGraph_CpG.bedGraph, V00297_methyldackel_CpG.bedGraph_CpG.bedGraph -c 10 -q 0.05 -o test-low-high -t 20 > methylasso1.log

and I got the following error:

Reading condition HIGH with 3 replicate(s) in memory.. Reading condition LOW with 3 replicate(s) in memory.. Error in fread(file_path) : Input is empty or only contains BOM or terminal control characters Calls: lapply -> FUN -> lapply -> FUN -> process_replicate -> fread Execution halted

The methyldackel files, should be fine. From the bismark files I got even the graphs, but I was shocked that according to methylKit, the depth is supposed to be ~ 30X; the graphs showed it to be less than 1X. I understand that bismark has a deduplication step, but that level of reduction was shocking.

I checked the methyldackel files, with used a bam files that had read deduplication by Picard, but MethylKit showed medium-high depth, and they look okay (methylasso) [juaguila@u05 Rec-5]$ head V00001_methyldackel_CpG.bedGraph_CpG.bedGraph NW_022882922.1 3064 3065 0 0 1 NW_022882922.1 3071 3072 0 0 1 NW_022882922.1 3804 3805 0 0 1 NW_022882922.1 3829 3830 0 0 1 NW_022882922.1 3839 3840 0 0 1 NW_022882922.1 3845 3846 0 0 1 NW_022882922.1 3847 3848 0 0 1 NW_022882922.1 3869 3870 0 0 1 NW_022882922.1 3912 3913 0 0 1 NW_022882922.1 4855 4856 0 0 2

(methylasso) [juaguila@u05 Rec-5]$ head V00297_methyldackel_CpG.bedGraph_CpG.bedGraph NW_022882922.1 4855 4856 0 0 5 NW_022882922.1 4865 4866 0 0 5 NW_022882922.1 4888 4889 0 0 6 NW_022882922.1 4891 4892 0 0 6 NW_022882922.1 4903 4904 0 0 7 NW_022882922.1 4952 4953 0 0 7 NW_022882922.1 4961 4962 0 0 6 NW_022882922.1 4965 4966 0 0 7 NW_022882922.1 4975 4976 0 0 7 NW_022882922.1 5048 5049 0 0 10

Any suggestion about what might be causing that error with the methyldackel files?

Thank you very much. I ran the analysis in a server with 48 cores and 500G of Ram.

delbala commented 7 months ago

Hi,

You have a typo on your both code, you have an extra space after the comma in the option --C2

To be able to answer you, I need to see what your input files look like. Can you give me a head of the file V00001.deduplicated.bismark.cov.gz and can you also tell me what the columns in file V00001_methyldackel_CpG.bedGraph_CpG.bedGraph correspond to ?

Best, Delphine

desmodus1984 commented 6 months ago

Hi Delphine

The head of V00001.deduplicated.bismark.cov.gz is

gzip -cd V00001.deduplicated.bismark.cov.gz | head NW_022882922.1 3066 3066 0 0 1 NW_022882922.1 3073 3073 0 0 1 NW_022882922.1 3131 3131 0 0 1 NW_022882922.1 3138 3138 0 0 1 NW_022882922.1 3158 3158 0 0 1 NW_022882922.1 3177 3177 0 0 1 NW_022882922.1 3405 3405 0 0 1 NW_022882922.1 3423 3423 0 0 1 NW_022882922.1 3453 3453 0 0 1 NW_022882922.1 3465 3465 0 0 1

The columns of V00001_methyldackel_CpG.bedGraph_CpG.bedGraph are

The chromosome/contig/scaffold name

The start coordinate

The end coordinate

The methylation percentage rounded to an integer

The number of alignments/pairs reporting methylated bases

The number of alignments/pairs reporting unmethylated bases

Let me know if you need further information.

Juan Pablo Aguilar Cabezas

From: Delphine Balaramane @.> Sent: Friday, April 5, 2024 7:53 AM To: abardet/methylasso @.> Cc: Aguilar Cabezas, Juan Pablo @.>; Author @.> Subject: [External] Re: [abardet/methylasso] Program doesn't run in conda (Issue #4)

Use caution with links and attachments.

Hi,

You have a typo on your both code, you have an extra space after the comma in the option --C2

To be able to answer you, I need to see what your input files look like. Can you give me a head of the file V00001.deduplicated.bismark.cov.gz and can you also tell me what the columns in file V00001_methyldackel_CpG.bedGraph_CpG.bedGraph correspond to ?

Best, Delphine

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delbala commented 1 month ago

Hi,

Unfortunately, I haven't been able to find a solution to your problem. I reviewed the input files, and they don't seem to have any apparent issues.

However, please ensure that the columns in your input files are properly separated by tabs, as incorrect delimiters can sometimes cause these errors. I would also suggest trying to rerun the code after addressing the typos mentioned earlier.

Delphine