fix: various issues to comply with CRAN submission

DESCRIPTION

@@ -7,7 +7,7 @@ Authors@R: c(
     person("Michael", "Jahn", , "jahn@mpusp.mpg.de", role = c("aut", "cph"),
            comment = c(ORCID = "0000-0002-3913-153X"))
   )
-Maintainer: Michael Jahn <jahn@mpusp.mpg.de>
+Maintainer: Yabing Song <songyb0519@gmail.com>
 Description: The goal of `ggcoverage` is to visualize coverage tracks from
     genomics, transcriptomics or proteomics data. It contains functions to
     load data from BAM, BigWig, BedGraph, txt, or xlsx files, create

R/FormatInput.R

@@ -34,7 +34,7 @@ GetRegion <- function(df, chr, start, end = NULL) {
 #'
 #' @param data Track dataframe loaded by \code{\link{LoadTrackFile}}.
 #' @param region Region used to create coverage plot, eg: chr14:21,677,306-21,737,601 or chr14:21,677,306.
-#' @param gtf.gr Granges object of GTF, created with \code{\link{import.gff}}. Default: NULL.
+#' @param gtf.gr Granges object of GTF, created with \code{\link[rtracklayer]{import.gff}}. Default: NULL.
 #' @param gene.name The name of gene. Default: HNRNPC.
 #' @param gene.name.type Gene name type (filed of \code{gtf.gr}), chosen from gene_name and gene_id.
 #' Default: gene_name.

R/LoadTrack.R

@@ -6,7 +6,7 @@
 #' @param region Region to extract coverage for, eg: chr14:21,677,306-21,737,601 or chr14:21,677,306.
 #'   Default: NULL, coverage is extracted from the first annotated chromosome/sequence.
 #' @param extend Extend length of \code{region}. Default: 2000.
-#' @param gtf.gr Granges object of GTF, created with \code{\link{import.gff}}. Default: NULL.
+#' @param gtf.gr Granges object of GTF, created with \code{\link[rtracklayer]{import.gff}}. Default: NULL.
 #' @param gene.name The name of gene. Default: HNRNPC.
 #' @param gene.name.type Gene name type (filed of \code{gtf.gr}), chosen from gene_name and gene_id.
 #'   Default: gene_name.

R/geom_base.R

@@ -18,13 +18,13 @@
 #' @param star.size The size of star when \code{mark.type} is star. Default: 1.
 #' @param show.aa Logical value, whether to show amino acid. Default: TRUE.
 #' @param sens Sense to translate: F for forward sense and R for reverse sense.
-#' Parameter of \code{\link{translate}}. Default: F.
+#' Parameter of \code{\link[Biostrings]{translate}}. Default: F.
 #' @param numcode The ncbi genetic code number for translation.
-#' Parameter of \code{\link{translate}}. By default the standard genetic code is used.
+#' Parameter of \code{\link[Biostrings]{translate}}. By default the standard genetic code is used.
 #' @param NAstring How to translate amino-acids when there are ambiguous bases in codons.
-#' Parameter of \code{\link{translate}}. Default: X.
+#' Parameter of \code{\link[Biostrings]{translate}}. Default: X.
 #' @param ambiguous If TRUE, ambiguous bases are taken into account so that for instance GGN is
-#' translated to Gly in the standard genetic code. Parameter of \code{\link{translate}}. Default: FALSE.
+#' translated to Gly in the standard genetic code. Parameter of \code{\link[Biostrings]{translate}}. Default: FALSE.
 #' @param aa.color Color scheme for amino acids.
 #' @param aa.border.color The border color of amino acid. Default: white.
 #' @param aa.size The size of amino acid text. Default: 4.

R/geom_gene.R

@@ -1,6 +1,6 @@
 #' Add Gene Annotation to Coverage Plot.
 #'
-#' @param gtf.gr Granges object of GTF, created with \code{\link{import.gff}}.
+#' @param gtf.gr Granges object of GTF, created with \code{\link[rtracklayer]{import.gff}}.
 #'   Default: NULL.
 #' @param overlap.gene.gap The gap between gene groups. Default: 0.1.
 #' @param overlap.style The style of gene groups, choose from loose (each gene

R/geom_transcript.R

@@ -1,6 +1,6 @@
 #' Add Transcript Annotation to Coverage Plot.
 #'
-#' @param gtf.gr Granges object of GTF, created with \code{\link{import.gff}}.
+#' @param gtf.gr Granges object of GTF, created with \code{\link[rtracklayer]{import.gff}}.
 #'   Default: NULL.
 #' @param gene.name Gene name of all transcripts. Default: HNRNPC.
 #' @param overlap.tx.gap The gap between transcript groups. Default: 0.1.

README.Rmd

@@ -471,7 +471,7 @@ graphics::mtext(
 graphics::par(opar)
 ```
 
-Default color scheme for amino acid annotation is from [Residual colours: a proposal for aminochromography](https://academic.oup.com/peds/article/10/7/743/1593029?login=false):
+Default color scheme for amino acid annotation is from [Residual colours: a proposal for aminochromography](https://pubmed.ncbi.nlm.nih.gov/9342138/):
 
 ```{r aa_color_scheme, warning = FALSE, fig.height = 9, fig.width = 10, fig.align = "center"}
 aa_color <- c(
@@ -678,7 +678,7 @@ The Hi-C method maps chromosome contacts in eukaryotic cells.
 For this purpose, DNA and protein complexes are cross-linked and DNA fragments then purified.
 As a result, even distant chromatin fragments can be found to interact due to the spatial organization of the DNA and histones in the cell. Hi-C data shows these interactions for example as a contact map.
 
-The Hi-C data is taken from [pyGenomeTracks: reproducible plots for multivariate genomic datasets](https://academic.oup.com/bioinformatics/article/37/3/422/5879987?login=false).
+The Hi-C data is taken from [pyGenomeTracks: reproducible plots for multivariate genomic datasets](https://pubmed.ncbi.nlm.nih.gov/32745185/).
 
 The Hi-C matrix visualization is implemented by [`HiCBricks`](https://github.com/koustav-pal/HiCBricks).
 This package needs to be installed separately (it is only 'Suggested' by `ggcoverage`).
@@ -788,7 +788,7 @@ basic_coverage +
 
 ### Load coverage
 
-The exported coverage from [Proteome Discoverer](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006021/):
+The exported coverage from [Proteome Discoverer](https://doi.org/10.3390/proteomes9010015):
 
 ```{r ms_coverage_data}
 library(openxlsx)

README.md

@@ -337,9 +337,6 @@ library(ggbio)
 #> 
 #>     geom_bar, geom_rect, geom_segment, ggsave, stat_bin, stat_identity,
 #>     xlim
-```
-
-``` r
 
 basic_coverage +
   geom_gene(gtf.gr = gtf_gr) +
@@ -459,9 +456,6 @@ library("BSgenome.Hsapiens.UCSC.hg19")
 #> The following object is masked from 'package:BiocIO':
 #> 
 #>     FileForFormat
-```
-
-``` r
 
 # create plot
 basic_coverage +
@@ -497,9 +491,6 @@ track_df <- LoadTrackFile(
   region = "4:1-160000000"
 )
 #> No metadata provided, returning coverage as is.
-```
-
-``` r
 
 # add chr prefix
 track_df$seqnames <- paste0("chr", track_df$seqnames)
@@ -606,9 +597,6 @@ track_df <- LoadTrackFile(
 #> No 'region' specified; extracting coverage for an example range
 #> (<=100,000 bases, first annotated sequence)
 #> Coverage extracted from sequence/chromosome: chr10
-```
-
-``` r
 
 head(track_df)
 #>   seqnames    start      end width strand score   Type  Group
@@ -669,7 +657,7 @@ graphics::par(opar)
 
 Default color scheme for amino acid annotation is from [Residual
 colours: a proposal for
-aminochromography](https://academic.oup.com/peds/article/10/7/743/1593029?login=false):
+aminochromography](https://doi.org/10.1093/protein/10.7.743):
 
 ``` r
 aa_color <- c(
@@ -910,7 +898,7 @@ a contact map.
 
 The Hi-C data is taken from [pyGenomeTracks: reproducible plots for
 multivariate genomic
-datasets](https://academic.oup.com/bioinformatics/article/37/3/422/5879987?login=false).
+datasets](https://doi.org/10.1093/bioinformatics/btaa692).
 
 The Hi-C matrix visualization is implemented by
 [`HiCBricks`](https://github.com/koustav-pal/HiCBricks). This package
@@ -931,9 +919,6 @@ track_df <- LoadTrackFile(
   extend = 0
 )
 #> No metadata provided, returning coverage as is.
-```
-
-``` r
 
 track_df$score <- ifelse(track_df$score < 0, 0, track_df$score)
 
@@ -1021,9 +1006,6 @@ library(HiCBricks)
 #> The following object is masked from 'package:Biostrings':
 #> 
 #>     pattern
-```
-
-``` r
 
 basic_coverage +
   geom_tad(
@@ -1066,7 +1048,7 @@ quality of the data.
 ### Load coverage
 
 The exported coverage from [Proteome
-Discoverer](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006021/):
+Discoverer](https://doi.org/10.3390/proteomes9010015):
 
 ``` r
 library(openxlsx)

vignettes/ggcoverage.Rmd

@@ -500,7 +500,7 @@ graphics::mtext(
 graphics::par(opar)
 ```
 
-Default color scheme for amino acid annotation is from [Residual colours: a proposal for aminochromography](https://academic.oup.com/peds/article/10/7/743/1593029?login=false):
+Default color scheme for amino acid annotation is from [Residual colours: a proposal for aminochromography](https://pubmed.ncbi.nlm.nih.gov/9342138/):
 
 ```{r aa_color_scheme, warning = FALSE, fig.height = 9, fig.width = 10, fig.align = "center"}
 aa_color <- c(
@@ -705,7 +705,7 @@ The Hi-C method maps chromosome contacts in eukaryotic cells.
 For this purpose, DNA and protein complexes are cross-linked and DNA fragments then purified.
 As a result, even distant chromatin fragments can be found to interact due to the spatial organization of the DNA and histones in the cell. Hi-C data shows these interactions for example as a contact map.
 
-The Hi-C data is taken from [pyGenomeTracks: reproducible plots for multivariate genomic datasets](https://academic.oup.com/bioinformatics/article/37/3/422/5879987?login=false).
+The Hi-C data is taken from [pyGenomeTracks: reproducible plots for multivariate genomic datasets](https://pubmed.ncbi.nlm.nih.gov/32745185/).
 
 The Hi-C matrix visualization is implemented by [`HiCBricks`](https://github.com/koustav-pal/HiCBricks).
 This package needs to be installed separately (it is only 'Suggested' by `ggcoverage`).
@@ -819,7 +819,7 @@ knitr::include_graphics("../man/figures/README-hic_coverage-1.png")
 
 ### Load coverage
 
-The exported coverage from [Proteome Discoverer](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006021/):
+The exported coverage from [Proteome Discoverer](https://pmc.ncbi.nlm.nih.gov/articles/PMC8006021/):
 
 ```{r ms_coverage_data, eval = FALSE}
 library(openxlsx)