It is a simple way to summarize and present your analysis results using R!Like tbl_summary(), tbl_regression() creates highly customizable analytic tables with sensible defaults.. copy code from a suggestion, however; they don't get ignored! Using external customization functions We have another vignette (Regularized Cox Regression) dedicated solely to fitting regularized Cox models with the glmnet package; please consult that vignette for details. PRROC - 2014. This is a dissection of the prolific function. R SNPassoc: SNPs-Based Whole Genome Association Studies. First, Rs terminology arguably runs counter to broader programming conventions, where the usual meaning of library is closer to what we mean by package. Heres how this might look on Windows: Heres a similar look on macOS (but your results may vary): In both cases we see two active libraries, consulted in this order: This setup is typical on Windows, but is something you usually need to opt into on macOS 3. ## [9] MatrixGenerics_1.4.2 matrixStats_0.60.0 Use Git or checkout with SVN using the web URL. The compareGroups package (Subirana, Sanz, and Vila 2014) allows users to create tables displaying results of univariate analyses, stratified or not by categorical variable groupings. bimod : Likelihood-ratio test for single cell feature expression, poisson : Likelihood ratio test assuming an underlying negative binomial distribution. This presents a redacted view of the package and its history, but, by definition, it includes everything that is essential. Go.Data uses an API for all interactions between the web front-end and smartphone applications used for data collection. In a vignette [12] that accompanies the survival package Therneau, Crowson and Atkinson demonstrate that the Karnofsky score (karno) is, in fact, time-dependent so the assumptions for the Cox model are not met. In order to make easier to navigate throught the document, an index with hyperlinks is inserted in the document. ), # submit the request, parse the response, and convert to a data frame, # use saved username/password from above to authorize, # save access token to allow subsequent API calls below, # export the linelist data frame to your system's clipboard, here("data", "linelists", "ebola_linelist.xlsx"), interaction between the googlesheets4 and tidyverse, http://api.ratings.food.gov.uk/Establishments, R-specific file types such as RDS and RData, An RDS file (.rds) stores a single R object such as a data frame. The workhorse function is prp. Since 4.0 version, export2md supports cbind.createTable class objects, i.e.when exporting stratified descriptive tables. package To illustrate how this package works we sampled 85% data from the participants in the PREDIMED study (Estruch et al. The sas.Rnw vignette has a discussion of compute time and takes too long to run, etc. By default, only the descriptives table is shown. The following plot contains some styling, and includes Clopper and Pearson (1934) exact method confidence intervals. For an example both of the value of the sites organization and information that is very useful to R users, see How to make a great R reproducible example?, which is also mentioned above. Even if a package is not developed on a public platform, you can visit its source in the unofficial, read-only mirror maintained by R-hub. Its functions import() and export() can handle many different file types (e.g. Some R Packages for ROC Curves Therefore, we have made it possible to print gtsummary tables with various engines. This chapter will start you on the road to package development by converting the implicit knowledge youve gained from using R packages into the explicit knowledge needed to create and modify them. ## loaded via a namespace (and not attached): ## [17] panc8.SeuratData_3.0.2 ifnb.SeuratData_3.1.0 Alluvial Plots in ggplot2 Jason Cory Brunson 2020-12-04. If we run a PCA on our object, using the variable genes we found in FindVariableFeatures() above, we see that while most of the variance can be explained by lineage, PC8 and PC10 are split on cell-cycle genes including TOP2A and MKI67.We will attempt to regress this signal from the data, so that cell-cycle heterogeneity does not contribute to PCA or downstream analysis. The result is the same as if the user first call compareGroups and then createTable. You can discover vignettes by accessing the help page for a package, or via the browseVignettes() function: the command browseVignettes() opens a list of vignettes from all of your installed packages in your browser, while browseVignettes(package=package-name) (e.g., browseVignettes(package="survival")) shows the vignettes, if any, for a particular package. You can read more about stringr in the [Strings and characters] page. By default, string matching by apropos() is case-insensitive. Survival Tables can easily be exported to CSV, LaTeX, HTML, PDF, Word or Excel, or inserted in R-markdown files to generate reports automatically. For demonstration purposes, we will be using the 2,700 PBMC object that is available via the SeuratData package). High-Performance 1.1 Package structure. Seurat A tag already exists with the provided branch name. I can have things like blocks of which.table: By default only the table with the descriptives is exported. Notice how are the SNPs coded, i.e.by the alleles. Seurat defines the essential components of alluvial plots as A large portion of the source is found in the noweb directory, and is based on gtsummary + R Markdown The gtsummary package was written to be a companion to the gt package from RStudio. The two most common HTTP methods are GET and POST but others could include PUT, DELETE, PATCH, etc. R HardyWeinberg: Graphical Tests for Hardy-Weinberg Equilibrium. Survival is a recommended package, and such packages can only depend on other recommended packages. relevant portion of that pdf file. R new function called descrTable has been implemented to build descriptive tables in a single step. If you are new to package development, you may have never seen a package in source form! Survival analysis We suggest to use the new mlr3 framework from now on and for future projects. Unfortunately skip = only accepts one integer value, not a range (e.g.2:10 does not work). Note that only frequencies are displayed. ## [31] bitops_1.0-7 spatstat.utils_2.1-0 cachem_1.0.5 The distinction between the two is important and useful as you get involved in package development. The built-in function install.packages() meets this need. Provides R6 objects for tasks, learners, resamplings, and measures. ## [46] spatstat.geom_2.1-0 yaml_2.2.1 reshape2_1.4.4 In just one statement it is possible to update an object of class compareGroups and createTable: Note that the compareGroups object (res) is updated, selecting only Female" participants, and the createTable class object (restab) is updated to add a column with the maximum available data for each explanatory variable. The resulting object is of class rbind.createTable, which can be subset but not updated. For demonstration purposes, we will be using the 2,700 PBMC object that is available via the SeuratData package). label: Used to cite tables in a LaTeX document. table1 package This is because rio is using a different function for the different file types (see table above). Examples: Files that drive package development, checking, and documentation, outside of CRANs purview. Plots differ according to whether the variable is continuous or categorical. This function performs differential gene expression testing for each dataset/group and combines the p-values using meta-analysis methods from the MetaDE R package. Plots also can be done according to grouping variable. ## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C Under the hood, this calls pkgbuild::build() and, ultimately, R CMD build, which is described further in the Building package tarballs section of Writing R Extensions. Online tutorial. With rio, you can use the export() function in a very similar way to import(). When importing data into R it is most likely that you will use GET. submission then the published CRAN version may be x.yy-1 or even x.yy-2 or 3.) You might not even have any source packages on your computer. We just discussed the library() function, whose name is inspired by what it does. ## [7] grid_4.1.0 BiocParallel_1.26.1 Rtsne_0.15 GitHub If nothing happens, download GitHub Desktop and try again. When you install, R x.y.z and prior to installing any add-on packages, use dir.create("~/Library/R/x.y/library") to set up a user library. Many R packages are developed in the open on GitHub (or GitLab or similar). ## Running under: Ubuntu 20.04.2 LTS alluvial diagram Separated summary tables by groups of cases and controls are displayed, and the last table corresponds to missingness test comparing non-available rates among groups. Blog. This vignette will walk a reader Braces may be used to specify multi-word terms; otherwise matches for individual words are included. In addition, plots of all analysed variables are shown. ## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C Work fast with our official CLI. In this case only a boxplot is shown for continuous variables: The object from compareGroups can later be updated. The design and functionality were originally inspired by the alluvial package and have benefitted from the feedback of many users. ## [13] ica_1.0-2 future_1.21.0 miniUI_0.1.1.1 Although I began with a few ideas about packages that I wanted to talk about, like ROCR and pROC, which I have found useful in the past, I decided to use Gbor Csrdis relatively new package pkgsearch to search through CRAN and see whats out there. Anyone who wants to study the methods is caption: The table caption for descriptives table and available data table. The results data frame has the following columns : If the ident.2 parameter is omitted or set to NULL, FindMarkers() will test for differentially expressed features between the group specified by ident.1 and all other cells. Note: no, No or NO will produce the same results; the coding is not case sensitive. If it is set to ", no caption is inserted. To remove the variable toevent and event from the analysis: To select some explanatory variables (e.g., age, sex and waist) and store results in an object of class compareGroups: Note: Although we have full data (n= 6324) for Age, Sex and Waist circumference, there are some missing data in Hormone-replacement therapy (probably male participants). Note: recall that data may be posted* on a website without an API, which may be easier to retrieve. Some R Packages for ROC Curves The command below will define the data frames column names as the combination (pasting together) of the first (true) headers with the value immediately underneath (in the first row). Stating, for example, sep = ";" table will be exported to csv with columns separated by ;. ## [21] SeuratData_0.2.1 SeuratObject_4.0.2 ## [1] parallel stats4 stats graphics grDevices utils datasets The functions in the rpart.plotR package plot rparttrees [6,7]. It inherits the class createTable. The httr package works well for handling HTTP requests in R. It requires little prior knowledge of Web APIs and can be used by people less familiar with software development terminology. Seurat The following plot uses Guangchuang Yus dlstats package to look at the download history for the six packages I selected to profile. 2.40-5 to 2.41-0. The API exchange is most commonly done through an HTTP request. We have another vignette (Regularized Cox Regression) dedicated solely to fitting regularized Cox models with the glmnet package; please consult that vignette for details. Seurat The affected files fall into two broad, semi-overlapping classes: Here is a non-exhaustive list of typical entries in the .Rbuildignore file for a package in the tidyverse: Note that the comments above must not appear in an actual .Rbuildignore file; they are included here only for exposition. It can install a package from source files, a bundle (a.k.a. Note that mean and standard deviation has two decimal places for age, while percentage in sex has been set to three decimal places. The nature of variables to be analyzed should be known, or at least which variables are to be used as categorical. If you want to distribute your package to an R user who doesnt have package development tools, youll need to provide a binary package. For example a posted CSV file may be accessible simply by providing the site URL to import() as described in the section on importing from Github.*. Machine learning in R. CRAN release site. Rpart and the stagec example are described in Atkinson and Therneau (1997), which is also distributed as a vignette of the rpart package. Details are available in the Installing packages section of R Installation and Administration.Just like with devtools::build(), devtools provides a wrapper function, devtools::install(), that makes this tool By default the name of the table is displayed for each set of columns. ## attached base packages: This is the source code for the "survival" package in R. It gets posted to the For example, install.packages() can move a package from the source, bundled, or binary states into the installed state. The help() function and ? or to be used by tydiverse and dplyr packages are supported. Machine learning in R. CRAN release site. ## [37] scales_1.1.1 gtable_0.3.0 globals_0.14.0 The rest of the devtools/remotes install_*() functions are aimed at making things that are technically possible with base tooling a bit easier or more explicit, such as install_version() which installs a specific version of a CRAN package. For this example, we will use data from the Mayo Clinic trial in primary biliary cirrhosis (PBC) of the liver found in the survival package. In this case you will want to write code that imports the most recent file. .Rdata files can store multiple R objects - for example multiple data frames, model results, lists, etc. R package Crosstables for descriptive analyses The package_search() function takes a text string as input and uses basic text mining techniques to search all of CRAN. ## [121] nlme_3.1-152 jsonlite_1.7.2 desc_1.3.0 complete documentation of the methods. It is a simple way to summarize and present your analysis results using R!Like tbl_summary(), tbl_regression() creates highly customizable analytic tables with sensible defaults.. This CRAN Task View contains a list of packages, grouped by topic, that are useful for high-performance computing (HPC) with R. In this context, we are defining high-performance computing rather loosely as just about anything related to pushing R a little further: using compiled code, parallel computing (in both explicit and implicit modes), working with large
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