Feat(50)-UI_improvement

.Rbuildignore

@@ -0,0 +1,2 @@
+^.*\.Rproj$
+^\.Rproj\.user$

.github/workflows/ci.yml

@@ -0,0 +1,45 @@
+name: R CI
+on:
+  push:
+    branches: [main, master, develop, test, fix/45-fix_ci_yaml]
+  pull_request:
+    branches: [main, master, develop, test, fix/45-fix_ci_yaml]
+
+jobs:
+  test-coverage:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Set up pdflatex
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y texlive-latex-base
+          sudo apt-get install texlive-fonts-extra 
+
+      - name: Set up R
+        uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - name: Install Dependencies
+        run: |
+          R -e 'install.packages(c("devtools", "covr", "ggplot2", "WriteXLS", "gridExtra", "Cairo"))'
+
+      - name: Build and test
+        run: |
+          R CMD build .  
+          R CMD check .
+        # R CMD check --as-cran *tar.gz 
+
+      - name: Run Tests and Generate Coverage
+        run: |
+          Rscript -e 'library(devtools); devtools::test()'
+          Rscript -e 'library(covr); covr::codecov()'
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v3
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

.travis.yml

@@ -1,8 +1,36 @@
 language: r
+sudo: false
 cache: packages
 
-r_github_packages:
-     - r-lib/covr
+branches:
+  only:
+    - main
+    - master
+    - develop
+    - test
+
+before_install:
+  - sudo apt-get update
+  - sudo apt-get install -y texlive-latex-base
+  - sudo apt-get install texlive-fonts-extra
+
+install:
+  - Rscript -e 'install.packages("covr")'
+  - R -e 'install.packages(c("devtools", "ggplot2", "WriteXLS", "gridExtra", "Cairo"))'
+
+script:
+  - R CMD build .
+  - R CMD check --as-cran *tar.gz
+  - Rscript -e 'library(devtools); devtools::test()'
+  - Rscript -e 'library(covr); covr::codecov()'
 
 after_success:
-     - Rscript -e 'covr::coveralls()'
+  - Rscript -e 'covr::codecov()'
+
+addons:
+  apt:
+    packages:
+      - libxml2-dev
+
+notifications:
+  email: false

DESCRIPTION

@@ -2,21 +2,22 @@ Package: samplyzer
 Title: What the Package Does (one line, title case)
 Version: 0.0.0.9000
 Authors@R: person("Xiao", "Li", email = "xiaoli@broadinstitute.org", role = c("aut", "cre"))
+Author: Xiao Li
+Maintainer: Xiao Li <xiaoli@broadinstitute.org>
 Description: What the package does (one paragraph).
 Depends: R (>= 3.3.2)
 License: What license is it under?
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 6.0.1.9000
+RoxygenNote: 7.2.3
 Suggests: knitr,
     rmarkdown,
     Cairo,
     testthat,
-    covr
-Remotes: r-lib/covr
 VignetteBuilder: knitr
 Imports: class (>= 7.3-14),
     ggplot2 (>= 2.2.1),
     WriteXLS (>= 4.0.0),
     grid (>= 3.3.2),
-    gridExtra (>= 2.2.1)
+    gridExtra (>= 2.2.1),
+    covr

NAMESPACE

@@ -8,18 +8,29 @@ S3method(flagSamples,sampleDataset)
 S3method(getAttr,sampleDataset)
 S3method(inferAncestry,default)
 S3method(inferAncestry,sampleDataset)
+S3method(outlierPlots,default)
+S3method(outlierPlots,sampleDataset)
 S3method(print,sampleDataset)
+S3method(sampleQcPlot,default)
 S3method(sampleQcPlot,sampleDataset)
 S3method(save,sampleDataset)
 S3method(setAttr,sampleDataset)
 S3method(sort,sampleDataset)
+export(GeomSplitViolin)
 export(PCplots)
 export(calZscore)
 export(flagSamples)
+export(geom_split_violin)
 export(getAttr)
 export(hasAttr)
 export(inferAncestry)
+export(multiplot)
+export(multiplotWithSharedLegend)
+export(outlierPlots)
+export(runQcExplorer)
 export(sampleDataset)
 export(sampleQcPlot)
 export(save)
+export(scatter)
 export(setAttr)
+importFrom(ggplot2,Geom)

R/S3Method.R

@@ -1,10 +1,15 @@
 #' Save an sds to a specific format
 #'
-#' Save an sds to tsv, RDS or excel format
+#' @description Save an sds to tsv, RDS or excel format
 #'
-#' @param sds
+#' @param sds sample dataset
+#' @param ... Additional arguments to be passed.
 #'
 #' @export
+#' @seealso{\link{sort.sampleDataset}}
+#' @seealso{\link{save.sampleDataset}}
+#' @seealso{\link{dim.sampleDataset}}
+#' @seealso{\link{print.sampleDataset}}
 
 save <-function(sds, ...) UseMethod('save')
 
@@ -36,7 +41,7 @@ save.sampleDataset <- function(sds, RDS = NULL, tsv = NULL, xls = NULL) {
 #'
 #' @param sds sample dataset
 #' @param by sort by which category
-#' @return an sample dataset sds with updated index
+#' @return A sample dataset `sds` with updated index.
 #'
 #' @export
 
@@ -49,15 +54,18 @@ sort.sampleDataset <- function(sds, by) {
 
 #' Show dimensions of sample dataset sds
 #'
-#' @param sds sample data set sds
+#' @param sds Sample dataset `sds`.
 #' @return a vector of rows and columns of the data frame of sample data set
 #'
 #' @export
-
 dim.sampleDataset <- function(sds){
   dim(sds$df)
 }
 
+#' Print information about the sample dataset `sds`.
+#'
+#' @param sds Sample dataset `sds`.
+#'
 #' @export
 print.sampleDataset <- function(sds) {
   cat("\nClass: SampleDataset\n",

R/calZscore.R

@@ -1,11 +1,18 @@
 #' Calculate z-score of a vector or QC metrics of a SampleDataset
 #'
-#' @description Calculate z-score of a vector or QC metrics of a SampleDataset,
-#'              see details in calZscore.default and calZscore.sampleDataset
-#' @return The form of the value returned by predict depends on the class of
-#'         its argument. See the documentation of the particular methods for
-#'         details of what is produced by that method.
+#' @description
+#' Calculate z-score of a vector or QC metrics of a SampleDataset.
+#'
+#' @param ... Additional arguments to be passed.
+#'
+#' @return
+#' The form of the value returned by predict depends on the class of
+#' its argument. See the documentation of the particular methods for
+#' details of what is produced by that method.
+#'
 #' @export
+#' @seealso{\link{calZscore.default}}
+#' @seealso{\link{calZscore.sampleDataset}}
 
 calZscore <- function(...) UseMethod("calZscore")
 
@@ -14,7 +21,7 @@ calZscore <- function(...) UseMethod("calZscore")
 #' @description Calculate z-scores of a vector
 #' @param x   a vector of values or a sample dataset object
 #' @param mad binary, whether use Median Absolute Deviation to calculate the
-#'            standard deviation
+#'            standard deviation.Default is TRUE.
 #' @return    a vector of z-scores
 #' @export
 
@@ -30,15 +37,13 @@ calZscore.default <- function(x, mad = T) {
 
 #' Calculate z-scores of QC metrics of a SampleDataset
 #'
-#' @param object a sampleDataset object
-#' @param strat optional, logical, variable or vector of attributes the sample
-#'              will be stratified by
-#' @param mad optional, binary, whether use Median Absolute Deviation to
-#'            calculate z-score or not, default is True
-#' @param qcMetrics optional, a vector of names of qc metrics to compute zscore
-#' @param maxVcfZ optional, logical, calculate to report maximun Vcf Zscore
-#' @return sampleDataset object, with additional attributes: zscoreBy, zscore
-#'         and maximumVcfZscore
+#' @param object a sampleDataset object.
+#' @param strat optional, logical, variable, or vector of attributes the sample
+#' will be stratified by.
+#' @param qcMetrics optional, a vector of names of QC metrics to compute z-score.
+#' @param mad optional, binary, whether to use Median Absolute Deviation to
+#' calculate z-score or not, default is TRUE.
+#' @param maxVcfZ optional, logical, calculate to report maximum Vcf Z-score.
 #' @export
 
 calZscore.sampleDataset <- function (

R/flagSamples.R

@@ -2,6 +2,8 @@
 #'
 #' Flag a sample from a data frame or a sampleDataset
 #' @export
+#' @seealso{\link{flagSamples.default}}
+#' @seealso{\link{flagSamples.sampleDataset}}
 
 flagSamples <- function(...) UseMethod('flagSamples')
 
@@ -21,6 +23,8 @@ flagSamples <- function(...) UseMethod('flagSamples')
 #'
 #' @return Return a data frame
 #' @export
+#' @seealso{\link{flagSamples}}
+#' @seealso{\link{flagSamples.sampleDataset}}
 
 flagSamples.default <- function (df, column, cutoff, greater) {
   column = as.character(column)
@@ -55,6 +59,8 @@ flagSamples.default <- function (df, column, cutoff, greater) {
 #'               based on z-score if not specified. Default value is NULL.
 #' @return an updated sample dataset sds with flags added.
 #' @export
+#' @seealso{\link{flagSamples.default}}
+#' @seealso{\link{flagSamples}}
 
 flagSamples.sampleDataset <- function(sds, cutoffs, zscore = NULL){
   # conditions

R/getAttr.R

@@ -1,18 +1,23 @@
 #' Get attributes of an sds
 #'
-#' @param sds sample dataset sds
+#' @param sds sample dataset
+#' @param attribute name of attribute to return
+#' @param showID whether to display sample IDs or not in the output data frame
+#'
+#' @return a data frame that contains values of specific attribute
 #' @export
+#'
+#' @seealso{\link{getAttr.sampleDataset}}
 
 getAttr <- function (sds, ...) UseMethod('getAttr', sds)
 
 #' Get attributes of a SampleDataset
 #'
 #' @param sds sample data set
 #' @param attribute name of attribute to return
-#' @param showID whether to display sample IDs or not in the output data fram
-#' @param return a data frame that contains values of specific attribute
+#' @param showID whether to display sample IDs or not in the output data frame
 #'
-#' @return data frame
+#' @return a data frame that contains values of specific attribute
 #' @export
 
 getAttr.sampleDataset <- function(sds, attribute, showID = F) {

R/inferAncestry.R

@@ -1,18 +1,28 @@
 #' Predict sample ancestry from genotype Principle Components
 #'
 #' Principle Components of genotypes with k nearest neighbours.
-#' @return Updated sample Dataset sds with inferredAncestry tag
+#'
+#' @param ... Additional parameters for future expansion.
+#' @return Updated sample Dataset sds with inferredAncestry tag.
 #' @export
+#'
+#' @seealso{\link{inferAncestry.sampleDataset}}
+#' @seealso{\link{inferAncestry.default}}
 
 inferAncestry <- function(...) UseMethod('inferAncestry')
 
-#' Infer anestry with KNN
+#' Infer ancestry with KNN
+#'
+#' @param testSet Matrix used for test.
+#' @param trainSet Matrix for training PCs.
+#' @param ancestry Ancestries corresponding to the training PCs.
+#' @param k Number of nearest neighbors to use in this classification.
 #'
-#' @param testSet matrix used for test
-#' @param trainSet matrix for training PCs
-#' @param ancestry ancestries correspond to the training PCs
-#' @param k Number of nearest neighbour to use in this classfication
+#' @return A vector of inferred ancestries.
 #' @export
+#'
+#' @seealso{\link{inferAncestry.sampleDataset}}
+#' @seealso{\link{inferAncestry}}
 
 inferAncestry.default <- function(testSet, trainSet, ancestry, k = 5) {
   inferredAncestry = class::knn(train = trainSet, test = testSet, cl = ancestry, k = k)
@@ -21,12 +31,16 @@ inferAncestry.default <- function(testSet, trainSet, ancestry, k = 5) {
 
 #' Infer sample ancestry
 #'
-#' @param sds Sample Dataset sds for Ancestry predition
-#' @param trainSet data frame with genotype PCs for each sample with known ancestry
-#' @param knownAncestry a vector with known ancestry for each sample in same order of trainSet
-#' @param nPC Use first n PCs to predict ancestry
+#' @param sds Sample Dataset sds for ancestry prediction.
+#' @param trainSet Data frame with genotype PCs for each sample with known ancestry.
+#' @param knownAncestry A vector with known ancestry for each sample in the same order as trainSet.
+#' @param nPC Use the first n PCs to predict ancestry.
 #'
+#' @return Updated sample Dataset sds with inferredAncestry tag.
 #' @export
+#'
+#' @seealso{\link{inferAncestry}}
+#' @seealso{\link{inferAncestry.default}}
 
 inferAncestry.sampleDataset <- function(
   sds, trainSet, knownAncestry, nPC = 3, k = 5