Search Results for "run code"

...To know more about the book, check out the About this book section below. You can read the current version of the book in your web browser. The book is built using the publishing system Quarto in conjunction with a little bit of R code (zig_engine.R), which is responsible for calling the Zig compiler to compile and run the Zig code examples.

...Number of toy datasets is available, the interactive application also allows the users to upload and analyze their own data and to automatically generate PDF or HTML reports. All methods include sample R code which is ready to copy and paste into R and run locally. Several toy data sets are ready to use. You can also upload and analyze your own data. ShinyItemAnalysis provides model equations, parameter estimates and their interpretation.

...It functions as the canonical source for course lab exercises, lecture modules, and reading materials in reproducible format. Students and learners use these R Markdown files to follow along, knit notebooks, run code samples, and complete the lab-based assignments. The repo is licensed under MIT, allowing reuse and modification. It is part of a larger ecosystem: the compiled HTML / book version of the labs is published via a companion “book” repository, which presents a polished, browsable version of the materials. The content covers topics such as data wrangling in R, statistical inference, genomics workflows, Bioconductor packages, and project-based analyses. ...

...It aims to demystify the bridge between textbook statistics and empirical modeling by walking through assumption checking, visualization, interpreting outputs, and pitfalls of misuse. Throughout, the content emphasizes clarity and accessibility, showing not just how to run statistical tests or build models, but what they mean and when one method is preferred over another.

...Peer-reviewed version is to be out soon. All other code is still the same for previous releases. The code should be run in full mode to obtain credible results. Not running a full run to estimate anything is not recommended and discouraged. Only a full run should be used to get results.

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. The version in that...