Be explicit about BiocSyle functions in vignettes

vignettes/practical_tips.Rmd

@@ -301,7 +301,7 @@ gather_tmp_h5 <- function(output_file, input) {
 }
 ```
 
-Finally we need to create a wrapper function that brings our split and gather functions together.  Like the `simple_writer()` function we created earlier, this takes the name of an output file and the list of datasets to be written as input.  We can also provide a `BiocParallelParam` instance from `r Biocpkg("BiocParallel")` to trial writing the temporary file in parallel.  If the `BPPARAM` argument isn't provided then they will be written in serial.
+Finally we need to create a wrapper function that brings our split and gather functions together.  Like the `simple_writer()` function we created earlier, this takes the name of an output file and the list of datasets to be written as input.  We can also provide a `BiocParallelParam` instance from `r BiocStyle::Biocpkg("BiocParallel")` to trial writing the temporary file in parallel.  If the `BPPARAM` argument isn't provided then they will be written in serial.
 
 ```{r, define-split-gather}
 split_and_gather <- function(output_file, input_dsets, BPPARAM = NULL) {

vignettes/rhdf5.Rmd

@@ -32,9 +32,9 @@ interface. On the other hand it provides high level convenience
 functions on **R** level to make a usage of HDF5 files more easy.
 
 #Installation of the HDF5 package
-To install the `r Biocpkg("rhdf5")` package, you need a current version
+To install the `r BiocStyle::Biocpkg("rhdf5")` package, you need a current version
 (>3.5.0) of **R** (www.r-project.org). After installing **R** you can
-run the following commands from the **R** command shell to install `r Biocpkg("rhdf5")`.
+run the following commands from the **R** command shell to install `r BiocStyle::Biocpkg("rhdf5")`.
 
 ```{r installation,eval=FALSE}
 install.packages("BiocManager")
@@ -149,7 +149,7 @@ h5closeAll()
 ```
 
 \subsection{Writing and reading with subsetting, chunking and compression}
-The `r Biocpkg("rhdf5")` package provides two ways of subsetting. One can
+The `r BiocStyle::Biocpkg("rhdf5")` package provides two ways of subsetting. One can
 specify the submatrix with the **R**-style index lists or with the HDF5
 style hyperslabs. Note, that the two next examples below show two
 alternative ways for reading and writing the exact same
@@ -314,7 +314,7 @@ file.size("myhdf5file.h5")
 
 **R** does not support a native datatype for 64-bit integers. All integers in **R** are
 32-bit integers. When reading 64-bit integers from a HDF5-file, you
-may run into troubles. `r Biocpkg("rhdf5")` is able to deal with 64-bit integers, but
+may run into troubles. `r BiocStyle::Biocpkg("rhdf5")` is able to deal with 64-bit integers, but
 you still should pay attention.
 
 As an example, we create an HDF5 file that contains 64-bit integers.
@@ -354,11 +354,11 @@ storage.mode(D64b)
 
 `bit64conversion='bit64'` is the recommended way of coercing. It
 represents the 64-bit integers as objects of class *integer64* as
-defined in the package `r CRANpkg("bit64")`. Make sure that you have installed
-`r CRANpkg("bit64")`.
+defined in the package `r BiocStyle::CRANpkg("bit64")`. Make sure that you have installed
+`r BiocStyle::CRANpkg("bit64")`.
 *The datatype *integer64* is not part of base **R**, but defined
 in an external package. This can produce unexpected behaviour when
-working with the data.* When choosing this option the package `r CRANpkg("bit64")`
+working with the data.* When choosing this option the package `r BiocStyle::CRANpkg("bit64")`
 will be loaded.
 
 ```{r bit64integer4}

vignettes/rhdf5_cloud_reading.Rmd

@@ -16,7 +16,7 @@ vignette: |
 knitr::opts_chunk$set(echo = TRUE)
 ```
 
-The `r Biocpkg("rhdf5")` provides limited support for read-only access to HDF5 files stored in Amazon S3 buckets.  This is implemented via the [HDF5 S3 Virtual File Driver](https://portal.hdfgroup.org/display/HDF5/Virtual+File+Drivers+-+S3+and+HDFS) and allows access to HDF5 files hosted in both public and private S3 buckets.  
+The `r BiocStyle::Biocpkg("rhdf5")` provides limited support for read-only access to HDF5 files stored in Amazon S3 buckets.  This is implemented via the [HDF5 S3 Virtual File Driver](https://portal.hdfgroup.org/display/HDF5/Virtual+File+Drivers+-+S3+and+HDFS) and allows access to HDF5 files hosted in both public and private S3 buckets.  
 
 Currently only the functions `h5ls()`, `h5dump()` and `h5read()` are supported.