inferCSN

Inferring Cell-Specific Gene Regulatory Network

v1.2.0 · Oct 15, 2025 · MIT + file LICENSE

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Description

An R package for inferring cell-type specific gene regulatory network from single-cell RNA-seq data.

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ERROR r-devel-macos-arm64

examples

Running examples in ‘inferCSN-Ex.R’ failed
The error most likely occurred in:

> ### Name: inferCSN
> ### Title: inferring cell-type specific gene regulatory network
> ### Aliases: inferCSN inferCSN,matrix-method inferCSN,sparseMatrix-method
> ###   inferCSN,data.frame-method
> 
> ### ** Examples
> 
> data(example_matrix)
> network_table_1 <- inferCSN(
+   example_matrix
+ )
ℹ [2026-02-13 15:27:47] Running for <dense matrix>.
◌ [2026-02-13 15:27:47] Checking input parameters...
ℹ [2026-02-13 15:27:47] Using `L0` sparse regression model
ℹ [2026-02-13 15:27:47] Using 1 core
ℹ [2026-02-13 15:27:47] Building results
✔ [2026-02-13 15:27:47] Run done.
> 
> network_table_2 <- inferCSN(
+   example_matrix,
+   cores = 2
+ )
ℹ [2026-02-13 15:27:47] Running for <dense matrix>.
◌ [2026-02-13 15:27:47] Checking input parameters...
ℹ [2026-02-13 15:27:47] Using `L0` sparse regression model
ℹ [2026-02-13 15:27:47] Using 2 cores

 *** caught segfault ***
address 0x110, cause 'invalid permissions'

 *** caught segfault ***
address 0x110, cause 'invalid permissions'

Traceback:
 1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...)
 2: doTryCatch(return(expr), name, parentenv, handler)
 3: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 4: tryCatchList(expr, classes, parentenv, handlers)
 5: 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))})
 6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...))
 7: fit_srm(x, y, cross_validation = cross_validation, seed = seed,     penalty = penalty, n_folds = n_folds, verbose = verbose,     ...)
 8: single_network(matrix = object, regulators = regulators, target = x,     cross_validation = cross_validation, seed = seed, penalty = penalty,     r_squared_threshold = r_squared_threshold, n_folds = n_folds,     verbose = verbose, ...)
 9: fun(x[[i]])
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, classes, parentenv, handlers)
13: tryCatch(fun(x[[i]]), error = function(e) {    structure(list(error = e$message, index = i, input = x[[i]]),         class = "parallelize_error")})
14: eval(c.expr, envir = args, enclos = envir)
15: eval(c.expr, envir = args, enclos = envir)
16: doTryCatch(return(expr), name, parentenv, handler)
17: tryCatchOne(expr, names, parentenv, handlers[[1L]])
18: tryCatchList(expr, classes, parentenv, handlers)
19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e)
20: FUN(X[[i]], ...)
21: lapply(X = S, FUN = FUN, ...)
22: doTryCatch(return(expr), name, parentenv, handler)
23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
24: tryCatchList(expr, classes, parentenv, handlers)
25: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE)
27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE))
28: FUN(X[[i]], ...)
29: lapply(seq_len(cores), inner.do)
30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,     mc.silent = silent, mc.cores = cores)
31: e$fun(obj, substitute(ex), parent.frame(), e$data)
32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar%     {        list(tryCatch(fun(x[[i]]), error = function(e) {            structure(list(error = e$message, index = i, input = x[[i]]),                 class = "parallelize_error")        }))    }
33: thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)
34: obj_check_list(x, call = error_call)
35: check_list_of_data_frames(x)
36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose))
37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets,     fun = function(x) {        single_network(matrix = object, regulators = regulators,             target = x, cross_validation = cross_validation,             seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold,             n_folds = n_folds, verbose = verbose, ...)    }, cores = cores, verbose = verbose)), abs_weight = FALSE)
38: inferCSN(example_matrix, cores = 2)
39: inferCSN(example_matrix, cores = 2)
An irrecoverable exception occurred. R is aborting now ...

Traceback:
 1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...)
 2: doTryCatch(return(expr), name, parentenv, handler)
 3: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 4: tryCatchList(expr, classes, parentenv, handlers)
 5: 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))})
 6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...))
 7: fit_srm(x, y, cross_validation = cross_validation, seed = seed,     penalty = penalty, n_folds = n_folds, verbose = verbose,     ...)
 8: single_network(matrix = object, regulators = regulators, target = x,     cross_validation = cross_validation, seed = seed, penalty = penalty,     r_squared_threshold = r_squared_threshold, n_folds = n_folds,     verbose = verbose, ...)
 9: fun(x[[i]])
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, classes, parentenv, handlers)
13: tryCatch(fun(x[[i]]), error = function(e) {    structure(list(error = e$message, index = i, input = x[[i]]),         class = "parallelize_error")})
14: eval(c.expr, envir = args, enclos = envir)
15: eval(c.expr, envir = args, enclos = envir)
16: doTryCatch(return(expr), name, parentenv, handler)
17: tryCatchOne(expr, names, parentenv, handlers[[1L]])
18: tryCatchList(expr, classes, parentenv, handlers)
19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e)
20: FUN(X[[i]], ...)
21: lapply(X = S, FUN = FUN, ...)
22: doTryCatch(return(expr), name, parentenv, handler)
23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
24: tryCatchList(expr, classes, parentenv, handlers)
25: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE)
27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE))
28: FUN(X[[i]], ...)
29: lapply(seq_len(cores), inner.do)
30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,     mc.silent = silent, mc.cores = cores)
31: e$fun(obj, substitute(ex), parent.frame(), e$data)
32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar%     {        list(tryCatch(fun(x[[i]]), error = function(e) {            structure(list(error = e$message, index = i, input = x[[i]]),                 class = "parallelize_error")        }))    }
33: thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)
34: obj_check_list(x, call = error_call)
35: check_list_of_data_frames(x)
36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose))
37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets,     fun = function(x) {        single_network(matrix = object, regulators = regulators,             target = x, cross_validation = cross_validation,             seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold,             n_folds = n_folds, verbose = verbose, ...)    }, cores = cores, verbose = verbose)), abs_weight = FALSE)
38: inferCSN(example_matrix, cores = 2)
39: inferCSN(example_matrix, cores = 2)
An irrecoverable exception occurred. R is aborting now ...
Warning in mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,  :
  scheduled cores 1, 2 did not deliver results, all values of the jobs will be affected

 *** caught segfault ***
address 0x110, cause 'invalid permissions'

 *** caught segfault ***
address 0x110, cause 'invalid permissions'

Traceback:
 1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...)
 2: doTryCatch(return(expr), name, parentenv, handler)
 3: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 4: tryCatchList(expr, classes, parentenv, handlers)
 5: 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))})
 6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...))
 7: fit_srm(x, y, cross_validation = cross_validation, seed = seed,     penalty = penalty, n_folds = n_folds, verbose = verbose,     ...)
 8: single_network(matrix = object, regulators = regulators, target = x,     cross_validation = cross_validation, seed = seed, penalty = penalty,     r_squared_threshold = r_squared_threshold, n_folds = n_folds,     verbose = verbose, ...)
 9: fun(x[[i]])
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, classes, parentenv, handlers)
13: tryCatch(fun(x[[i]]), error = function(e) {    structure(list(error = e$message, index = i, input = x[[i]]),         class = "parallelize_error")})
14: eval(c.expr, envir = args, enclos = envir)
15: eval(c.expr, envir = args, enclos = envir)
16: doTryCatch(return(expr), name, parentenv, handler)
17: tryCatchOne(expr, names, parentenv, handlers[[1L]])
18: tryCatchList(expr, classes, parentenv, handlers)
19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e)
20: FUN(X[[i]], ...)
21: lapply(X = S, FUN = FUN, ...)
22: doTryCatch(return(expr), name, parentenv, handler)
23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
24: tryCatchList(expr, classes, parentenv, handlers)
25: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE)
27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE))
28: FUN(X[[i]], ...)
29: lapply(seq_len(cores), inner.do)
30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,     mc.silent = silent, mc.cores = cores)
31: e$fun(obj, substitute(ex), parent.frame(), e$data)
32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar%     {        list(tryCatch(fun(x[[i]]), error = function(e) {            structure(list(error = e$message, index = i, input = x[[i]]),                 class = "parallelize_error")        }))    }
33: thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)
34: obj_check_list(x, call = error_call)
35: check_list_of_data_frames(x)
36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose))
37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets,     fun = function(x) {        single_network(matrix = object, regulators = regulators,             target = x, cross_validation = cross_validation,             seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold,             n_folds = n_folds, verbose = verbose, ...)    }, cores = cores, verbose = verbose)), abs_weight = FALSE)
38: inferCSN(example_matrix, cores = 2)
39: inferCSN(example_matrix, cores = 2)
An irrecoverable exception occurred. R is aborting now ...

Traceback:
 1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...)
 2: doTryCatch(return(expr), name, parentenv, handler)
 3: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 4: tryCatchList(expr, classes, parentenv, handlers)
 5: 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))})
 6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num,     ...))
 7: fit_srm(x, y, cross_validation = cross_validation, seed = seed,     penalty = penalty, n_folds = n_folds, verbose = verbose,     ...)
 8: single_network(matrix = object, regulators = regulators, target = x,     cross_validation = cross_validation, seed = seed, penalty = penalty,     r_squared_threshold = r_squared_threshold, n_folds = n_folds,     verbose = verbose, ...)
 9: fun(x[[i]])
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, classes, parentenv, handlers)
13: tryCatch(fun(x[[i]]), error = function(e) {    structure(list(error = e$message, index = i, input = x[[i]]),         class = "parallelize_error")})
14: eval(c.expr, envir = args, enclos = envir)
15: eval(c.expr, envir = args, enclos = envir)
16: doTryCatch(return(expr), name, parentenv, handler)
17: tryCatchOne(expr, names, parentenv, handlers[[1L]])
18: tryCatchList(expr, classes, parentenv, handlers)
19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e)
20: FUN(X[[i]], ...)
21: lapply(X = S, FUN = FUN, ...)
22: doTryCatch(return(expr), name, parentenv, handler)
23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
24: tryCatchList(expr, classes, parentenv, handlers)
25: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call, nlines = 1L)        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        sm <- strsplit(conditionMessage(e), "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE)
27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE))
28: FUN(X[[i]], ...)
29: lapply(seq_len(cores), inner.do)
30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,     mc.silent = silent, mc.cores = cores)
31: e$fun(obj, substitute(ex), parent.frame(), e$data)
32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar%     {        list(tryCatch(fun(x[[i]]), error = function(e) {            structure(list(error = e$message, index = i, input = x[[i]]),                 class = "parallelize_error")        }))    }
33: thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)
34: obj_check_list(x, call = error_call)
35: check_list_of_data_frames(x)
36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) {    single_network(matrix = object, regulators = regulators,         target = x, cross_validation = cross_validation, seed = seed,         penalty = penalty, r_squared_threshold = r_squared_threshold,         n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose))
37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets,     fun = function(x) {        single_network(matrix = object, regulators = regulators,             target = x, cross_validation = cross_validation,             seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold,             n_folds = n_folds, verbose = verbose, ...)    }, cores = cores, verbose = verbose)), abs_weight = FALSE)
38: inferCSN(example_matrix, cores = 2)
39: inferCSN(example_matrix, cores = 2)
An irrecoverable exception occurred. R is aborting now ...
Warning in mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed,  :
  scheduled cores 1, 2 did not deliver results, all values of the jobs will be affected
ℹ [2026-02-13 15:27:47] Building results
Error in names(output_list) <- x : attempt to set an attribute on NULL
Calls: inferCSN ... check_list_of_data_frames -> obj_check_list -> <Anonymous>
Execution halted

OK r-devel-windows-x86_64

OK r-oldrel-macos-arm64

OK r-oldrel-macos-x86_64

OK r-oldrel-windows-x86_64

OK r-patched-linux-x86_64

OK r-release-linux-x86_64

OK r-release-macos-arm64

OK r-release-macos-x86_64

OK r-release-windows-x86_64

Check History

ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 9, 2026

ERROR r-devel-macos-arm64

examples

Running examples in ‘inferCSN-Ex.R’ failed
The error most likely occurred in:

> ### Name: inferCSN
> ### Title: inferring cell-type specific gene regulatory network
> ### Aliases: inferCSN inferCSN,matrix-method inferCSN,sparseMatrix-method
> ###   inferCSN,data.frame-method
> 
> ### ** Examples
> 
> data(example_matrix)
> network_table_1 <- inferCSN(
+   example_matrix
+ )
ℹ [2026-02-13 15:27:47] Running for <dense matrix>.
◌ [2026-02-13 15:27:47] Checking input parameters...
ℹ [2026-02-13 15:

Dependency Network

Version History

new 1.2.0 Mar 9, 2026