diff --git a/DESCRIPTION b/DESCRIPTION
index 71e2d74..1368c5e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,8 +2,8 @@ Encoding: UTF-8
 Package: bigsnpr
 Type: Package
 Title: Analysis of Massive SNP Arrays
-Version: 1.12.14
-Date: 2024-09-10
+Version: 1.12.15
+Date: 2024-09-20
 Authors@R: c(
     person("Florian", "Privé", email = "florian.prive.21@gmail.com", role = c("aut", "cre")),
     person("Michael", "Blum", role = "ths"),
diff --git a/R/apply-parallelize.R b/R/apply-parallelize.R
index e01caa0..7cd5ca5 100644
--- a/R/apply-parallelize.R
+++ b/R/apply-parallelize.R
@@ -10,10 +10,10 @@
 #'
 #' @inheritParams bigsnpr-package
 #' @param FUN The function to be applied. It must take a
-#' [FBM.code256][FBM.code256-class] as first argument and `ind.chr`,
+#' [FBM.code256][bigstatsr::FBM.code256-class] as first argument and `ind.chr`,
 #' an another argument to provide subsetting over SNPs.
 #' You can access the number of the chromosome by using `attr(ind.chr, "chr")`.
-#' @param combine function that is used by [foreach] to process the tasks
+#' @param combine function that is used by [foreach::foreach] to process the tasks
 #' results as they generated. This can be specified as either a function or a
 #' non-empty character string naming the function. Specifying 'c' is useful
 #' for concatenating the results into a vector, for example. The values 'cbind'
diff --git a/R/bigSNP-class.R b/R/bigSNP-class.R
index 44f5aa1..a13fd82 100644
--- a/R/bigSNP-class.R
+++ b/R/bigSNP-class.R
@@ -19,7 +19,7 @@ CODE_DOSAGE <- c(0, 1, 2, NA, 0, 1, 2, seq(0, 2, by = 0.01), rep(NA, 48))
 #' An S3 class for representing information on massive SNP arrays.
 #'
 #' @return A named list with at least 3 slots: \describe{
-#'   \item{genotypes}{A [FBM.code256][FBM.code256-class] which is
+#'   \item{genotypes}{A [FBM.code256][bigstatsr::FBM.code256-class] which is
 #'     a special Filebacked Big Matrix encoded with type `raw` (one byte
 #'     unsigned integer), representing genotype calls and possibly imputed
 #'     allele dosages. Rows are individuals and columns are SNPs.}
diff --git a/R/external-software.R b/R/external-software.R
index 4d617ed..ae548ac 100644
--- a/R/external-software.R
+++ b/R/external-software.R
@@ -601,7 +601,7 @@ snp_plinkKINGQC <- function(plink2.path,
 #' @param plink.options Other options to be passed to PLINK as a string. More
 #'   options can be found at \url{https://www.cog-genomics.org/plink2/filter}.
 #' @param ncores Number of cores used. Default doesn't use parallelism.
-#'   You may use [nb_cores].
+#'   You may use [bigstatsr::nb_cores()].
 #'
 #' @references Browning, Brian L., and Sharon R. Browning.
 #' "Genotype imputation with millions of reference samples."
diff --git a/R/ldsc.R b/R/ldsc.R
index fb5dab9..0b97994 100644
--- a/R/ldsc.R
+++ b/R/ldsc.R
@@ -173,7 +173,6 @@ snp_ldsc <- function(ld_score, ld_size, chi2, sample_size,
 #'     when using a mixed model, the effective sample size needs to be adjusted
 #'     as well, see \doi{10.1016/j.xhgg.2022.100136}.
 #' @param ind.beta Indices in `corr` corresponding to `df_beta`. Default is all.
-#' @inheritDotParams snp_ldsc chi2_thr1 chi2_thr2
 #'
 #' @export
 #'
@@ -195,7 +194,8 @@ snp_ldsc2 <- function(corr, df_beta,
                       intercept = 1,
                       ncores = 1,
                       ind.beta = cols_along(corr),
-                      ...) {
+                      chi2_thr1 = 30,
+                      chi2_thr2 = Inf) {
 
   assert_df_with_names(df_beta, c("beta", "beta_se", "n_eff"))
   assert_lengths(ind.beta, rows_along(df_beta))
@@ -218,7 +218,8 @@ snp_ldsc2 <- function(corr, df_beta,
     blocks      = blocks,
     intercept   = intercept,
     ncores      = ncores,
-    ...
+    chi2_thr1   = chi2_thr1,
+    chi2_thr2   = chi2_thr2
   )
 }
 
diff --git a/R/modify-positions.R b/R/modify-positions.R
index 24e0afe..713bd68 100644
--- a/R/modify-positions.R
+++ b/R/modify-positions.R
@@ -163,16 +163,19 @@ snp_asGeneticPos <- function(infos.chr, infos.pos, dir = tempdir(), ncores = 1,
 
 #' Download a genetic map
 #'
-#' @param type Which genetic map to download. The hg19 ones are downloaded from
-#' \url{https://github.com/joepickrell/1000-genomes-genetic-maps/} while the
-#' hg38 is downloaded from
-#' \url{https://alkesgroup.broadinstitute.org/Eagle/downloads/tables/}.
+#' @param type Which genetic map to download.
 #' @param dir Directory where to download and decompress files.
 #' @inheritParams bigsnpr-package
 #'
 #' @return A data frame with 3 columns: `chr`, `pos`, and `pos_cM`.
 #' @export
 #'
+#' @details
+#' The hg19 genetic maps are downloaded from
+#' \url{https://github.com/joepickrell/1000-genomes-genetic-maps/}
+#' while the hg38 one is downloaded from
+#' `https://alkesgroup.broadinstitute.org/Eagle/downloads/tables/`.
+#'
 #' @rdname snp_asGeneticPos2
 #'
 download_genetic_map <- function(type = c("hg19_OMNI", "hg19_hapmap", "hg38_price"),
diff --git a/R/read-bgen.R b/R/read-bgen.R
index 56b9db5..cf7366e 100644
--- a/R/read-bgen.R
+++ b/R/read-bgen.R
@@ -122,7 +122,7 @@ check_bgen_format <- function(bgenfile) {
 #'   file, and use e.g. `match()` to get indices corresponding to the ones you want.
 #'
 #' @param ncores Number of cores used. Default doesn't use parallelism.
-#'   You may use [nb_cores()].
+#'   You may use [bigstatsr::nb_cores()].
 #' @param read_as How to read BGEN probabilities? Currently implemented:
 #'   - as dosages (rounded to two decimal places), the default,
 #'   - as hard calls, randomly sampled based on those probabilities
diff --git a/man/bigSNP-class.Rd b/man/bigSNP-class.Rd
index 911900e..f528494 100644
--- a/man/bigSNP-class.Rd
+++ b/man/bigSNP-class.Rd
@@ -6,7 +6,7 @@
 \title{Class bigSNP}
 \value{
 A named list with at least 3 slots: \describe{
-\item{genotypes}{A \link[=FBM.code256-class]{FBM.code256} which is
+\item{genotypes}{A \link[bigstatsr:FBM.code256-class]{FBM.code256} which is
 a special Filebacked Big Matrix encoded with type \code{raw} (one byte
 unsigned integer), representing genotype calls and possibly imputed
 allele dosages. Rows are individuals and columns are SNPs.}
diff --git a/man/snp_asGeneticPos2.Rd b/man/snp_asGeneticPos2.Rd
index 029b8a3..34c9a5b 100644
--- a/man/snp_asGeneticPos2.Rd
+++ b/man/snp_asGeneticPos2.Rd
@@ -14,10 +14,7 @@ download_genetic_map(
 snp_asGeneticPos2(infos.chr, infos.pos, genetic_map)
 }
 \arguments{
-\item{type}{Which genetic map to download. The hg19 ones are downloaded from
-\url{https://github.com/joepickrell/1000-genomes-genetic-maps/} while the
-hg38 is downloaded from
-\url{https://alkesgroup.broadinstitute.org/Eagle/downloads/tables/}.}
+\item{type}{Which genetic map to download.}
 
 \item{dir}{Directory where to download and decompress files.}
 
@@ -43,3 +40,9 @@ The new vector of genetic positions.
 This function uses linear interpolation, whereas \code{snp_asGeneticPos()} uses
 nearest neighbors.
 }
+\details{
+The hg19 genetic maps are downloaded from
+\url{https://github.com/joepickrell/1000-genomes-genetic-maps/}
+while the hg38 one is downloaded from
+\verb{https://alkesgroup.broadinstitute.org/Eagle/downloads/tables/}.
+}
diff --git a/man/snp_beagleImpute.Rd b/man/snp_beagleImpute.Rd
index 34bec9a..af37d3a 100644
--- a/man/snp_beagleImpute.Rd
+++ b/man/snp_beagleImpute.Rd
@@ -30,7 +30,7 @@ appending \code{"_impute"} to \code{prefix.in} (\code{bedfile.in} without extens
 to be an integer. Default is \code{3}.}
 
 \item{ncores}{Number of cores used. Default doesn't use parallelism.
-You may use \link{nb_cores}.}
+You may use \code{\link[bigstatsr:reexports]{bigstatsr::nb_cores()}}.}
 
 \item{extra.options}{Other options to be passed to Beagle as a string. More
 options can be found at Beagle's website.}
diff --git a/man/snp_ldsc.Rd b/man/snp_ldsc.Rd
index d654821..5231e4e 100644
--- a/man/snp_ldsc.Rd
+++ b/man/snp_ldsc.Rd
@@ -24,7 +24,8 @@ snp_ldsc2(
   intercept = 1,
   ncores = 1,
   ind.beta = cols_along(corr),
-  ...
+  chi2_thr1 = 30,
+  chi2_thr2 = Inf
 )
 }
 \arguments{
@@ -72,12 +73,6 @@ as well, see \doi{10.1016/j.xhgg.2022.100136}.
 }}
 
 \item{ind.beta}{Indices in \code{corr} corresponding to \code{df_beta}. Default is all.}
-
-\item{...}{
-  Arguments passed on to \code{\link[=snp_ldsc]{snp_ldsc}}
-  \describe{
-    \item{\code{}}{}
-  }}
 }
 \value{
 Vector of 4 values (or only the first 2 if \code{blocks = NULL}):
diff --git a/man/snp_prodBGEN.Rd b/man/snp_prodBGEN.Rd
index 9b1142e..a155a7b 100644
--- a/man/snp_prodBGEN.Rd
+++ b/man/snp_prodBGEN.Rd
@@ -45,7 +45,7 @@ file, and use e.g. \code{match()} to get indices corresponding to the ones you w
 Default is \code{1000}.}
 
 \item{ncores}{Number of cores used. Default doesn't use parallelism.
-You may use \code{\link[=nb_cores]{nb_cores()}}.}
+You may use \code{\link[bigstatsr:reexports]{bigstatsr::nb_cores()}}.}
 }
 \value{
 The product \code{bgen_data[ind_row, 'list_snp_id'] \%*\% beta}.
diff --git a/man/snp_readBGEN.Rd b/man/snp_readBGEN.Rd
index e46db43..75b91ae 100644
--- a/man/snp_readBGEN.Rd
+++ b/man/snp_readBGEN.Rd
@@ -43,7 +43,7 @@ file, and use e.g. \code{match()} to get indices corresponding to the ones you w
 }}
 
 \item{ncores}{Number of cores used. Default doesn't use parallelism.
-You may use \code{\link[=nb_cores]{nb_cores()}}.}
+You may use \code{\link[bigstatsr:reexports]{bigstatsr::nb_cores()}}.}
 }
 \value{
 The path to the RDS file \verb{<backingfile>.rds} that stores the \code{bigSNP}
diff --git a/man/snp_split.Rd b/man/snp_split.Rd
index 6e3bde6..87aeb47 100644
--- a/man/snp_split.Rd
+++ b/man/snp_split.Rd
@@ -11,11 +11,11 @@ snp_split(infos.chr, FUN, combine, ncores = 1, ...)
 Typically \verb{<bigSNP>$map$chromosome}.}
 
 \item{FUN}{The function to be applied. It must take a
-\link[=FBM.code256-class]{FBM.code256} as first argument and \code{ind.chr},
+\link[bigstatsr:FBM.code256-class]{FBM.code256} as first argument and \code{ind.chr},
 an another argument to provide subsetting over SNPs.
 You can access the number of the chromosome by using \code{attr(ind.chr, "chr")}.}
 
-\item{combine}{function that is used by \link{foreach} to process the tasks
+\item{combine}{function that is used by \link[foreach:foreach]{foreach::foreach} to process the tasks
 results as they generated. This can be specified as either a function or a
 non-empty character string naming the function. Specifying 'c' is useful
 for concatenating the results into a vector, for example. The values 'cbind'