Fixed doc for enPamGb and DeepCpf1

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: crisprScore
-Version: 1.9.2
-Date: 2024-07-28
+Version: 1.9.3
+Date: 2024-10-03
 Title: On-Target and Off-Target Scoring Algorithms for CRISPR gRNAs
 Authors@R: c(
     person("Jean-Philippe", "Fortin", email = "[email protected]", role = c("aut", "cre", "cph")),
@@ -41,7 +41,7 @@ Description:
     Note that DeepHF, DeepCpf1 and enPAM+GB are not available on Windows machines. 
 License: MIT + file LICENSE
 Encoding: UTF-8
-RoxygenNote: 7.2.1
+RoxygenNote: 7.3.2
 VignetteBuilder: knitr
 StagedInstall: no
 BugReports: https://github.com/crisprVerse/crisprScore

R/getDeepCpf1Scores.R

@@ -10,7 +10,7 @@
 #' 
 #' @details The input sequences for DeepCpf1 scoring require 4 nucleotides
 #'     upstream of the protospacer sequence, the protospacer sequence
-#'     itself (4bp PAM sequence + 23bp spacer sequence) and 3 nucleootides 
+#'     itself (4bp PAM sequence + 23bp spacer sequence) and 3 nucleotides 
 #'     downstream of the protospacer sequence, for a total of 34 nucleotides.
 #'     If \code{convertPAM} is set to \code{TRUE}, any non-canonical PAM
 #'     sequence will be convert to TTTC for scoring purposes.
@@ -28,10 +28,10 @@
 #' 
 #' @examples
 #' if (interactive()){
-#' flank5 <- "ACC" #3bp
+#' flank5 <- "ACCG" #4bp
 #' pam    <- "TTTT" #4bp
 #' spacer <- "AATCGATGCTGATGCTAGATATT" #23bp
-#' flank3 <- "AAGT" #4bp
+#' flank3 <- "AAG" #4bp
 #' input  <- paste0(flank5, pam, spacer, flank3) 
 #' results <- getDeepCpf1Scores(input)
 #' }

inst/NEWS.Rd

@@ -3,6 +3,11 @@
 \encoding{UTF-8}
 
 
+\section{Version 1.9.3}{\itemize{
+\item Fixed documentation for enPamGB and DeepCpf1 algorithms. 
+}}
+
+
 \section{Version 1.9.2}{\itemize{
 \item Fixed python environments based on the lastest changes in basilisk (using conda-forge installations).
 }}

vignettes/crisprScore.Rmd

@@ -357,15 +357,15 @@ knitr::include_graphics("./figures/sequences_cas12a.svg")
 The DeepCpf1 algorithm is an on-target cutting efficiency prediction algorithm 
 for the Cas12a nuclease [@deepcpf1] using a convolutional neural network (CNN) 
 framework. It generates a score between 0 and 1 to quantify the likelihood of 
-Cas12a to cut for a given sgRNA. 3 nucleotides upstream and 4 nucleotides 
-downstream of the PAM sequence are needed for scoring:
+Cas12a to cut for a given sgRNA. 4 nucleotides upstream of the PAM sequence, and 3 nucleotides 
+downstream of the protospacer sequence are needed for scoring:
 
 
 ```{r, eval=FALSE}
-flank5 <- "ACC" #3bp
+flank5 <- "ACCA" #4bp
 pam    <- "TTTT" #4bp
 spacer <- "AATCGATGCTGATGCTAGATATT" #23bp
-flank3 <- "AAGT" #4bp
+flank3 <- "AAG" #3bp
 input  <- paste0(flank5, pam, spacer, flank3) 
 results <- getDeepCpf1Scores(input)
 ```
@@ -378,14 +378,16 @@ for the enhanced Cas12a (enCas12a) nuclease [@enpamgb] using a gradient-booster
 comparison to the wildtype Cas12 nuclease [@encas12a], and the enPAM+GB 
 algorithm takes PAM activity into account in the calculation of the final score.
 It generates a probability (therefore a score between 0 and 1) of a given sgRNA 
-to cut at the intended target. 3 nucleotides upstream of the PAM sequence and 4 nucleotides downstream of the protospacer sequence are needed for scoring:
+to cut at the intended target. 4 nucleotides upstream of the PAM
+sequence, and 3 nucleotides downstream of the protospacer
+sequence are needed for scoring:
 
 
 ```{r, eval=FALSE}
-flank5 <- "ACC" #3bp
+flank5 <- "ACCG" #4bp
 pam    <- "TTTT" #4bp
 spacer <- "AATCGATGCTGATGCTAGATATT" #23bp
-flank3 <- "AAGT" #4bp
+flank3 <- "AAG" #3bp
 input  <- paste0(flank5, pam, spacer, flank3) 
 results <- getEnPAMGBScores(input)
 ```