[Review]: High-dimensional Statistics

[gperu]

Lesson Title

High-dimensional Statistics with R

Lesson Repository URL

https://github.com/carpentries-incubator/high-dimensional-stats-r

Lesson Website URL

https://carpentries-incubator.github.io/high-dimensional-stats-r/

Lesson Description

This course is intended for those who have a working knowledge of statistics and linear models with R and wish to learn high-dimensional statistical methods with R.

This is a short course aimed at familiarising learners with statistical and computational methods for the extremely high-dimensional data commonly found in biomedical and health sciences (e.g., gene expression, DNA methylation, health records). These datasets can be challenging to approach, as they often contain many more features than observations, and it can be difficult to distinguish meaningful patterns from natural underlying variability. To this end, we will introduce and explain a range of methods and approaches to disentangle these patterns from natural variability. After completion of this course, learners will be able to understand, apply, and critically analyse a broad range of statistical methods. In particular, we focus on providing a strong grounding in high-dimensional regression, dimensionality reduction, and clustering.

Author Usernames

@alanocallaghan
@catavallejos
@ailithewing

Zenodo DOI

No response

Differences From Existing Lessons

No response

Confirmation of Lesson Requirements

• is the original work of the author(s), or that any content derived from another source is reused with permission and appropriate attribution
• aligns with The Carpentries Code of Conduct
• is published under a CC-BY or CC0 license
• uses The Carpentries lesson template or Carpentries Workbench without significant customisation/adaptation.

JOSE Submission Requirements

• the lesson repository includes paper.md and paper.bib files as described in the JOSE submission guide for learning modules

Potential Reviewers

No response

[tobyhodges]

Thank you for submitting this lesson for review, @gperu.

My capacity for managing lesson reviews is quite limited at the moment and I will not be able to handle reviews of all of your submitted lessons simultaneously. If you have a preference for which lesson(s) you would like us to prioritise for review, please let me know and I will do my best to focus on that/those first.

[catavallejos]

Thanks @tobyhodges and @gperu. Probably good to keep this course towards the end. @hannesbecher and I are working on some final changes to incorporate some of the feedback we have received during delivery. I will add a note here when ready.

[catavallejos]

@gperu could you please add @hannesbecher as an author? I can't edit the issue.

[catavallejos]

Hi @tobyhodges and @gperu. @hannesbecher and I completed our last round of planned changes so these materials are now ready to be reviewed. Please let me know what do we need to do to get the process started.

Best
Cata

[catavallejos]

Note that I cannot edit the original post in this thread to add additional authors or suggest reviewers

[mallewellyn]

Hi @tobyhodges, following further community reviews and changes, we would like to re-submit the lesson for review if at all possible. We totally understand that your capacity for reviews is limited. In case this helps, we have documented our community reviews, changes made in response to these reviews, and how we conform to The Carpentries' requirements here.

[Fgazzelloni]

Editor checks on-going 🤚

Editor Checklist - High-dimensional Statistics

Accessibility

• All figures are also described in image alternative text or elsewhere in the lesson body.

• The lesson uses appropriate heading levels:

  • h2 is used for sections within a page.
  • no "jumps" are present between heading levels e.g. h2->h4.
  • no page contains more than one h1 element i.e. none of the source files include first-level headings.

• The contrast ratio of text in all figures is at least 4.5:1.

• replace this with any further comments relating to the accessibility of the lesson.

Content

• The lesson teaches data and/or computational skills that could promote efficient, open, and reproducible research.

• All exercises have solutions.

• Opportunities for formative assessments are included and distributed throughout the lesson sufficiently to track learner progress. (We aim for at least one formative assessment every 10-15 minutes.)

• Any data sets used in the lesson are published under a permissive open license i.e. CC0 or equivalent.

• replace this with any further comments relating to the lesson content.

Design

• Learning objectives are defined for the lesson and every episode.

• The target audience of the lesson is identified specifically and in sufficient detail.

• replace this with any further comments relating to the design of the lesson.

Repository

The lesson repository includes:

• a CC-BY or CC0 license.

• a CODE_OF_CONDUCT.md file that links to The Carpentries Code of Conduct.

• a list of lesson maintainers.

• tabs to display Issues and Pull Requests for the project.

• replace this with any further comments relating to the lesson repository.

Structure

• Estimated times are included in every episode for teaching and completing exercises.
• Episodes lengths are appropriate for the management of cognitive load throughout the lesson.

Supporting information

The lesson includes:

• a list of required prior skills and/or knowledge.
• setup and installation instructions.
• a glossary of key terms or links out to definitions in an external glossary e.g. Glosario.

General

• replace this with any other comments that do not fit into any of the previous sections.