replace all http:// with https://

daattali · Apr 1, 2023 · bdcb8df · bdcb8df
1 parent 9231cce
commit bdcb8df
Show file tree

Hide file tree

Showing 8 changed files with 22 additions and 21 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -39,4 +39,5 @@ Suggests:
     utils
 License: MIT + file LICENSE
 VignetteBuilder: knitr
-RoxygenNote: 7.1.0
+RoxygenNote: 7.2.3
+Encoding: UTF-8
diff --git a/R/ddpcr.R b/R/ddpcr.R
@@ -2,16 +2,16 @@
 ## Copyright (C) 2015 Dean Attali
 
 #' Analysis and visualization of Droplet Digital PCR data.
-#' 
+#'
 #' An interface to explore, analyze, and visualize droplet digital PCR
 #' (ddPCR) data in R. This is the first known non-proprietary software for
 #' analyzing ddPCR data. An interactive tool was also created and is available
 #' online to facilitate this analysis for anyone who is not comfortable with
 #' using R.\cr\cr
-#' \href{http://daattali.com/shiny/ddpcr/}{Use the web tool} or
+#' \href{https://daattali.com/shiny/ddpcr/}{Use the web tool} or
 #' \href{https://github.com/daattali/ddpcr}{read the full documentation on GitHub}.
-#' 
+#'
 #' @docType package
 #' @importFrom magrittr %<>%
 #' @name ddpcr
-NULL
+NULL
diff --git a/README.md b/README.md
@@ -3,15 +3,15 @@ ddpcr: Analysis and visualization of Droplet Digital PCR data in R and on the we
 
 [![R Build Status](https://github.com/daattali/ddpcr/workflows/R-CMD-check/badge.svg)](https://github.com/daattali/ddpcr/actions)
 [![CRAN
-version](http://www.r-pkg.org/badges/version/ddpcr)](https://cran.r-project.org/package=ddpcr)
+version](https://www.r-pkg.org/badges/version/ddpcr)](https://cran.r-project.org/package=ddpcr)
 
-> Created by [Dean Attali](http://deanattali.com)
+> Created by [Dean Attali](https://deanattali.com)
 
 This package provides an interface to explore, analyze, and visualize
 droplet digital PCR (ddPCR) data in R. It also includes an interactive
 web application with a visual user interface to facilitate analysis for
 anyone who is not comfortable with using R. The app is [available
-online](http://daattali.com/shiny/ddpcr/) or it can be [run
+online](https://daattali.com/shiny/ddpcr/) or it can be [run
 locally](#r-interactive).
 
 This document explains the purpose of this package and includes a
@@ -200,7 +200,7 @@ Analysis using the interactive tool
 </h1>
 If you’re not comfortable using R and would like to use a visual tool
 that requires no programming, you can [use the tool
-online](http://daattali.com/shiny/ddpcr/). You should still skim through
+online](https://daattali.com/shiny/ddpcr/). You should still skim through
 the rest of this document (you can ignore the actual code/commands) as
 it will explain some important concepts.
 

diff --git a/cran-comments.md b/cran-comments.md
@@ -12,7 +12,7 @@
 
 2016-02-18
 
-R CMD check passed with 0 warnings or errors, and notes about the provided sample data being large (4MB) and an invalid URL that will be valid once the package is on CRAN (http://cran.r-project.org/package=ddpcr)
+R CMD check passed with 0 warnings or errors, and notes about the provided sample data being large (4MB) and an invalid URL that will be valid once the package is on CRAN (https://cran.r-project.org/package=ddpcr)
 
 ### Reviewer comments
 
@@ -79,7 +79,7 @@ Added cran-comments to buildignore
 We also see
 
 Found the following (possibly) invalid URLs:
-  URL: http://cran.r-project.org/package=ddpcr
+  URL: https://cran.r-project.org/package=ddpcr
     From: inst/doc/overview.html
     Status: 404
     Message: Not Found

diff --git a/inst/shiny/text/about.md b/inst/shiny/text/about.md
@@ -20,9 +20,9 @@ This tool is part of a package developed in the R programming language. For more
 
 A peer-reviewed publication describing this tool is available in <a target="_blank" href="https://f1000research.com/articles/5-1411/">F1000Research</a>.
 
-The methods were originally developed for a paper <a target="_blank" href="http://jmd.amjpathol.org/article/S1525-1578(15)00262-7/">"Quantitative Detection and Resolution of BRAF V600 Status in Colorectal Cancer Using Droplet Digital PCR and a Novel Wild-Type Negative Assay"</a> by Roza Bidshahri, Dean Attali, et al. The sample data is also from the same project. 
+The methods were originally developed for a paper <a target="_blank" href="https://jmd.amjpathol.org/article/S1525-1578(15)00262-7/">"Quantitative Detection and Resolution of BRAF V600 Status in Colorectal Cancer Using Droplet Digital PCR and a Novel Wild-Type Negative Assay"</a> by Roza Bidshahri, Dean Attali, et al. The sample data is also from the same project. 
 
 ## License
 
-This software was developed by <a target="_blank" href="http://deanattali.com" >Dean Attali</a> and is available freely under the MIT license. The source code is available <a target="_blank" href="https://github.com/daattali/ddpcr">on GitHub</a>.  
-For any comments or questions, please <a target="_blank" href="http://deanattali.com/contact">contact Dean</a>.
+This software was developed by <a target="_blank" href="https://deanattali.com" >Dean Attali</a> and is available freely under the MIT license. The source code is available <a target="_blank" href="https://github.com/daattali/ddpcr">on GitHub</a>.  
+For any comments or questions, please <a target="_blank" href="https://deanattali.com/contact">contact Dean</a>.
diff --git a/man/ddpcr.Rd b/man/ddpcr.Rd
diff --git a/vignettes/algorithm.Rmd b/vignettes/algorithm.Rmd
@@ -15,7 +15,7 @@ knitr::opts_chunk$set(tidy = FALSE, comment = "#>")
 
 # Algorithms used to analyze ddPCR droplets
 
-The algorithm described below consists of five main steps that are used to analyze a ddPCR assay with (FAM+)/(FAM+HEX+) clusters. Droplets in the (FAM+HEX+) cluster will be referred to as *wildtype*, and droplets in the (FAM+HEX-) cluster will be referred to as *mutant*. The final goal is to calculate the mutant frequency (*MF*) in each well by classifying all template-containing droplets as wildtype or mutant. A more detailed explanation of the algorithm is available in Chapter 2 of [my MSc thesis](http://hdl.handle.net/2429/57928). 
+The algorithm described below consists of five main steps that are used to analyze a ddPCR assay with (FAM+)/(FAM+HEX+) clusters. Droplets in the (FAM+HEX+) cluster will be referred to as *wildtype*, and droplets in the (FAM+HEX-) cluster will be referred to as *mutant*. The final goal is to calculate the mutant frequency (*MF*) in each well by classifying all template-containing droplets as wildtype or mutant. A more detailed explanation of the algorithm is available in Chapter 2 of [my MSc thesis](https://hdl.handle.net/2429/57928). 
 
 Assays with (HEX+)/(FAM+HEX+) clusters use a very similar algorithm but HEX and FAM are swapped in every step. Assays that are neither (FAM+)/(FAM+HEX+) nor (HEX+)/(FAM+HEX+) only benefit from the first three steps of the pipeline (droplet gating is not performed). 
 
@@ -92,4 +92,4 @@ As an example, a well with 500 filled droplets that includes 7 mutant droplets i
 
 Mutant wells have clearly defined clusters of mutant and wildtype droplets, making it easy to determine where to gate them. On the other hand, wildtype wells have very few (if any) mutant droplets, making it difficult to accurately identify them. It is possible to leverage the data in mutant wells to get a more accurately find mutant droplets in wildtype wells. This is only possible if there are enough wells to draw data from, so this step only runs if there are at least *n* mutant wells in the plate (*n* = `(plate, 'RECLASSIFY', 'MIN_WELLS_NEGATIVE_CLUSTER')`, default is 4).
 
-The idea is to see where the mutant cluster is located relative to the wildtype cluster in most wells, and assume that wildtype wells are distributed similarly. To measure this feature, a special *mutant-to-wildtype ratio* is calculated for every mutant well by comparing the HEX value of the right-most mutant droplet to the median HEX value of the wildtype droplets (*mutant-to-wildtype ratio = max(mutant) / median(wildtype)*). After calculating this ratio for all mutant wells and obtaining a list of such ratios, a single value is used as the "consensus" ratio by choosing a certain percentile from the list (`params(plate, 'RECLASSIFY', 'BORDER_RATIO_QUANTILE'))`, default is 75).  The median HEX value of filled droplets in each wildtype well is multiplied by the consensus mutant-to-wildtype ratio, and the resulting value is used as the new border between mutant and wildtype droplets.
+The idea is to see where the mutant cluster is located relative to the wildtype cluster in most wells, and assume that wildtype wells are distributed similarly. To measure this feature, a special *mutant-to-wildtype ratio* is calculated for every mutant well by comparing the HEX value of the right-most mutant droplet to the median HEX value of the wildtype droplets (*mutant-to-wildtype ratio = max(mutant) / median(wildtype)*). After calculating this ratio for all mutant wells and obtaining a list of such ratios, a single value is used as the "consensus" ratio by choosing a certain percentile from the list (`params(plate, 'RECLASSIFY', 'BORDER_RATIO_QUANTILE'))`, default is 75).  The median HEX value of filled droplets in each wildtype well is multiplied by the consensus mutant-to-wildtype ratio, and the resulting value is used as the new border between mutant and wildtype droplets.
diff --git a/vignettes/overview.Rmd b/vignettes/overview.Rmd
@@ -17,11 +17,11 @@ options(ddpcr.verbose = TRUE)
 # ddpcr: Analysis and visualization of Droplet Digital PCR data in R and on the web
 
 [![R Build Status](https://github.com/daattali/ddpcr/workflows/R-CMD-check/badge.svg)](https://github.com/daattali/ddpcr/actions)
-[![CRAN version](http://www.r-pkg.org/badges/version/ddpcr)](https://cran.r-project.org/package=ddpcr)
+[![CRAN version](https://www.r-pkg.org/badges/version/ddpcr)](https://cran.r-project.org/package=ddpcr)
 
-> Created by [Dean Attali](http://deanattali.com)
+> Created by [Dean Attali](https://deanattali.com)
 
-This package provides an interface to explore, analyze, and visualize droplet digital PCR (ddPCR) data in R. It also includes an interactive web application with a visual user interface to facilitate analysis for anyone who is not comfortable with using R.  The app is [available online](http://daattali.com/shiny/ddpcr/) or it can be [run locally](#r-interactive).
+This package provides an interface to explore, analyze, and visualize droplet digital PCR (ddPCR) data in R. It also includes an interactive web application with a visual user interface to facilitate analysis for anyone who is not comfortable with using R.  The app is [available online](https://daattali.com/shiny/ddpcr/) or it can be [run locally](#r-interactive).
 
 This document explains the purpose of this package and includes a tutorial on how to use it. It should take about 20 minutes to go through the entire document. A peer-reviewed publication describing this tool is available in [F1000Research](https://f1000research.com/articles/5-1411/).
 
@@ -107,7 +107,7 @@ If your ddPCR experiment is not a **PNPP** type, you can still use this tool for
 
 <h1 id="analysis-interactive">Analysis using the interactive tool</h1>
 
-If you're not comfortable using R and would like to use a visual tool that requires no programming, you can [use the tool online](http://daattali.com/shiny/ddpcr/). You should still skim through the rest of this document (you can ignore the actual code/commands) as it will explain some important concepts.
+If you're not comfortable using R and would like to use a visual tool that requires no programming, you can [use the tool online](https://daattali.com/shiny/ddpcr/). You should still skim through the rest of this document (you can ignore the actual code/commands) as it will explain some important concepts.
 
 <h1 id="analysis-r">Analysis using R</h1>