@@ -1,7 +1,7 @@

 Package: idpr

 Type: Package

 Title: Profiling and Analyzing Intrinsically Disordered Proteins in R

-Version: 1.6.1

+Version: 1.6.11

 Authors@R: c(person(c("William", "M."), "McFadden", 

                 email = "wmm27@pitt.edu", 

                 role = c("cre", "aut")),

@@ -25,7 +25,7 @@ LazyData: true

 biocViews: StructuralPrediction, Proteomics, CellBiology

 RoxygenNote: 7.1.2

 Depends: 

-    R (>= 4.1.3)

+    R (>= 4.1.0)

 Imports: 

     ggplot2 (>= 3.3.0),

     magrittr (>= 1.5),

@@ -226,7 +226,7 @@ chargeCalculationGlobal <- function(

 #'   or vector of single characters.

 #'   It also supports a single character string that specifies

 #'   the location of a .fasta or .fa file.

-#' @param window a positive, odd integer. 7 by default.

+#' @param window a positive, odd integer. 9 by default.

 #'   Sets the size of sliding window, must be an odd number.

 #'   The window determines the number of residues to be analyzed and averaged

 #'   for each position along the sequence.

@@ -297,7 +297,7 @@ chargeCalculationGlobal <- function(

 #'  plot(gg)

-chargeCalculationLocal <- function(sequence, window = 7,  proteinName = NA,

+chargeCalculationLocal <- function(sequence, window = 9,  proteinName = NA,

                         pH = 7.0, pKaSet = "IPC_protein",

                         printCitation = FALSE, plotResults = FALSE, ...) {

     seqVector <- sequenceCheck(sequence = sequence, method = "stop",

@@ -45,7 +45,6 @@

 #' @references Kyte, J., & Doolittle, R. F. (1982). A simple method for

 #'   displaying the hydropathic character of a protein.

 #'   Journal of molecular biology, 157(1), 105-132.

-#' @export

 #' @section Plot Colors:

 #'   For users who wish to keep a common aesthetic, the following colors are

 #'   used when plotResults = TRUE. \cr

@@ -69,31 +68,14 @@

 #'   conditions?. Proteins: structure, function, and bioinformatics, 41(3),

 #'   415-427.

 #'   \url{https://doi.org/10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7}

-#' @examples

-#' #Amino acid sequences can be character strings

-#' aaString <- "ACDEFGHIKLMNPQRSTVWY"

-#' #Amino acid sequences can also be character vectors

-#' aaVector <- c("A", "C", "D", "E", "F",

-#'               "G", "H", "I", "K", "L",

-#'               "M", "N", "P", "Q", "R",

-#'               "S", "T", "V", "W", "Y")

-#' #Alternatively, .fasta files can also be used by providing

-#'   ##The path to the file as a character string.

-#'

-#'

-#' foldIndexR(aaVector)

-#'

-#' exampleDF <- 

-#'   foldIndexR(aaString,

-#'       plotResults = FALSE)

-#' head(exampleDF)

-#' 

+#' @export

 foldIndexR <- function(sequence,

                        window = 51, 

                        proteinName = NA,

                        pKaSet = "IPC_protein",

-                       plotResults = TRUE) {

+                       plotResults = TRUE,

+                       ...) {

     chargeDF <-

         chargeCalculationLocal(sequence = sequence, window = window,

@@ -25,7 +25,7 @@

 #' @param uniprotAccession character string specifying the UniProt Accession of

 #'   the protein of interest. Used to fetch predictions from IUPreds REST API.

 #'   Default is NA. Keep as NA if you do not have a UniProt Accession.

-#' @param window a positive, odd integer. 51 by default.

+#' @param window a positive, odd integer. 9 by default.

 #'   Sets the size of sliding window, must be an odd number.

 #'   The window determines the number of residues to be analyzed and averaged

 #'   for each position along the sequence. 51 is default for 

@@ -174,7 +174,7 @@ idprofile <- function(

     uniprotAccession = NA,

     proteinName = NA,

     iupredType = "long",

-    window = 51,

+    window = 9,

     pH = 7.2,

     pKaSet = "IPC_protein",

     structuralTendencyType = "bar",

@@ -199,12 +199,6 @@ idprofile <- function(

         plotResults = TRUE,

         pKaSet = pKaSet,

         proteinName = proteinName)

-    hydropPlot <- scaledHydropathyLocal(

-        sequence = sequence,

-        window = window,

-        plotResults = TRUE,

-        pKaSet = pKaSet,

-        proteinName = proteinName)

     tendencyPlot <- structuralTendencyPlot(

         sequence = sequence,

         graphType = structuralTendencyType,

@@ -5,7 +5,7 @@

 #'   showing the calculated scores for each window along the sequence.

 #' @inheritParams sequenceCheck

 #'

-#' @param window a positive, odd integer. 7 by default.

+#' @param window a positive, odd integer. 9 by default.

 #'   Sets the size of sliding window, must be an odd number.

 #'   The window determines the number of residues to be analyzed and averaged

 #'   for each position along the sequence.

@@ -44,7 +44,7 @@ if (!requireNamespace("BiocManager", quietly = TRUE))

 BiocManager::install("idpr")

 ```

-You can install the development version from 

+Additionally, you can install the development version from 

 [Bioconductor](https://bioconductor.org/packages/devel/bioc/html/idpr.html) 

 with:

 ``` r

@@ -28,7 +28,7 @@ if (!requireNamespace("BiocManager", quietly = TRUE))

 BiocManager::install("idpr")

 ```

-You can install the development version from

+Additionally, you can install the development version from

 [Bioconductor](https://bioconductor.org/packages/devel/bioc/html/idpr.html)

 with:

@@ -109,7 +109,7 @@ citation("idpr")

 #> 

 #>   William M. McFadden and Judith L. Yanowitz (2020). idpr: Profiling

 #>   and Analyzing Intrinsically Disordered Proteins in R. R package

-#>   version 1.6.1.

+#>   version 1.6.11.

 #> 

 #> A BibTeX entry for LaTeX users is

 #> 

@@ -117,7 +117,7 @@ citation("idpr")

 #>     title = {idpr: Profiling and Analyzing Intrinsically Disordered Proteins in R},

 #>     author = {William M. McFadden and Judith L. Yanowitz},

 #>     year = {2020},

-#>     note = {R package version 1.6.1},

+#>     note = {R package version 1.6.11},

 #>   }

 ```

@@ -125,9 +125,9 @@ citation("idpr")

 ``` r

 Sys.time()

-#> [1] "2022-03-11 02:31:26 EST"

+#> [1] "2022-03-15 20:07:30 EDT"

 Sys.Date()

-#> [1] "2022-03-11"

+#> [1] "2022-03-15"

 R.version

 #>                _                           

 #> platform       x86_64-apple-darwin17.0     

@@ -6,7 +6,7 @@

 \usage{

 chargeCalculationLocal(

   sequence,

-  window = 7,

+  window = 9,

   proteinName = NA,

   pH = 7,

   pKaSet = "IPC_protein",

@@ -21,7 +21,7 @@ or vector of single characters.

 It also supports a single character string that specifies

 the location of a .fasta or .fa file.}

-\item{window}{a positive, odd integer. 7 by default.

+\item{window}{a positive, odd integer. 9 by default.

 Sets the size of sliding window, must be an odd number.

 The window determines the number of residues to be analyzed and averaged

 for each position along the sequence.}

Binary files a/man/figures/README-example-3.png and b/man/figures/README-example-3.png differ

Binary files a/man/figures/README-example-4.png and b/man/figures/README-example-4.png differ

Binary files a/man/figures/README-example-5.png and b/man/figures/README-example-5.png differ

@@ -9,7 +9,8 @@ foldIndexR(

   window = 51,

   proteinName = NA,

   pKaSet = "IPC_protein",

-  plotResults = TRUE

+  plotResults = TRUE,

+  ...

 )

 }

 \arguments{

@@ -96,26 +97,6 @@ This is used to calculate the prediction of intrinsic disorder based on

   \url{https://doi.org/10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7}

 }

-\examples{

-#Amino acid sequences can be character strings

-aaString <- "ACDEFGHIKLMNPQRSTVWY"

-#Amino acid sequences can also be character vectors

-aaVector <- c("A", "C", "D", "E", "F",

-              "G", "H", "I", "K", "L",

-              "M", "N", "P", "Q", "R",

-              "S", "T", "V", "W", "Y")

-#Alternatively, .fasta files can also be used by providing

-  ##The path to the file as a character string.

-

-

-foldIndexR(aaVector)

-

-exampleDF <- 

-  foldIndexR(aaString,

-      plotResults = FALSE)

-head(exampleDF)

-

-}

 \references{

 Kyte, J., & Doolittle, R. F. (1982). A simple method for

   displaying the hydropathic character of a protein.

@@ -43,7 +43,7 @@ disorder based on environmental conditions. Regions of predicted

 environmental sensitivity are highlighted. See the respective functions

 for more details. This is skipped if uniprotAccession = NA.}

-\item{window}{a positive, odd integer. 51 by default.

+\item{window}{a positive, odd integer. 9 by default.

 Sets the size of sliding window, must be an odd number.

 The window determines the number of residues to be analyzed and averaged

 for each position along the sequence. 51 is default for 

@@ -18,7 +18,7 @@ a vector of single characters, or an AAString object.

 It also supports a single character string that specifies

 the path to a .fasta or .fa file.}

-\item{window}{a positive, odd integer. 7 by default.

+\item{window}{a positive, odd integer. 9 by default.

 Sets the size of sliding window, must be an odd number.

 The window determines the number of residues to be analyzed and averaged

 for each position along the sequence.}