Search Results for "tutorial"

...Currently, the package supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Please refer to the overview tutorial vignette for an introduction to psychmeta’s functions and workflows. psychmeta is hosted on both CRAN and GitHub. Documentation for psychmeta’s functions is available in the package’s PDF manual. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more.

In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. ...

Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. Harmony has been tested on R versions =4. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on Linux, OS X, and Windows platforms.

...The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc. Lessons and content are stored locally or can be downloaded and used without a continuous internet connection. Content includes quizzes, multiple-choice questions, coding exercises etc. to reinforce learning.

rnaseq_tutorial is a tutorial and educational resource created by the Griffith Lab that guides users through the steps of RNA-seq data analysis. It includes working pipelines for alignment, differential expression, alternative splicing, visualization, and interpretation. It is designed to run in the cloud or local environments, providing introductory material on file formats, reference genomes / annotation, QC, mapping, quantifying expression, visualizing results, etc.