Luke Rasmussen | UCSC OSPO

StatWrap

Thu, 29 Jan 2026 00:00:00 +0000

StatWrap is a free and open-source assistive, non-invasive discovery and inventory tool to document research projects. It inventories project assets (e.g., code files, data files, manuscripts, documentation) and organizes information without additional input from the user. It also provides structure for users to add searchable and filterable notes connected to files to help communicate metadata about intent and analysis steps.

At its core, StatWrap helps investigators identify and track changes in a research project as it evolves - which may affect reproducibility. For example: (1) people on the project can change over time, so processes may not be consistently executed due to transitions in employment; (2) data changes over time, due to accruing additional cases, adding new variables, or correcting mistakes in existing data; (3) software (e.g. used for data preparation and statistical analysis) evolves as it is edited, improved, and optimized; and (4) software can break or produce different results due to changes ‘under the hood’ such as updates to statistical packages, compilers, or interpreters. StatWrap passively and actively documents these changes to support reproducibility.

Additional information:

Group and Individual Customizations

Topics: configuration, user interface
Skills: JavaScript, React
Difficulty: Medium
Size: Large (350 hours)
Mentor: Luke Rasmussen, Eric Whitley

The goal of this project is to expand the existing capabilities of StatWrap to provide more flexibility to individual users and groups. Currently, features within StatWrap such as the directory template for creating new projects and the reproducibility checklist are static, meaning everyone who downloads StatWrap has the same configuration. However, each user and team work differently and should be able to configure StatWrap to support their needs.

When a user creates a new project, StatWrap provides a collection of project templates. These create a directory hierarchy, along with some seed files (e.g., a README.md file in the project root). Different groups have their own conventions for creating project directories. While StatWrap can be released with additional project templates defined, there are many situations in which users would want to keep their project template local. StatWrap should allow a user to create a project template configuration, from scratch or being seeded by the contents of an existing project. A user should then be able to export this configuration, share it with others, and other user should have the ability to import the configuration into their instance of StatWrap.

Similarly, StatWrap provides a reproducibility checklist that includes six existing checklist items. However, individual users and groups may have their own checklists, including institution-specific steps. Similar to the project template, a user should be able to configure additional items for the checklist. A user should be able to create a “checklist template” that can be used and applied in multiple projects. A specific project’s template should also be modifiable once the checklist has been created.

The specific tasks of the project include:

Developing a configuration scheme for New Project templates
Provide a way for a user to import/export a template for New Projects
Develop a configuration scheme for Reproducibility Checklist questions
Provide a way for a user to import/export a template for the Reproducibility Checklist
Develop a configuration scheme for asset (file) attributes
Develop unit tests and conduct system testing

StatWrap

Sun, 09 Feb 2025 00:00:00 +0000

Additional information:

Project Search

Topics: search, user interface, indexing
Skills: JavaScript, React
Difficulty: Medium
Size: Large (350 hours)
Mentor: Luke Rasmussen, Eric Whitley

The goal of this project is to leverage the information entered by users and passively discovered by StatWrap to facilitate cross-project searching. This functionality will allow investigators to search across projects (current and past) to find relevant projects, assets, and notes. Given the potentially sensitive nature of data included in projects, the indexing of content for searching must be done locally.

The specific tasks of the project include:

Identify and evaluate open-source projects to index content for searching
Add a new classification for projects of “Active” and “Past” in the user interface
Implement the search capability within the user interface
Develop unit tests and conduct system testing

StatWrap

Wed, 24 Jan 2024 00:00:00 +0000

Additional information:

Reproducibility Checklists

Topics: reproducibility, user interface, checklists
Skills: JavaScript, React
Difficulty: Medium
Size: Large (350 hours)
Mentor: Luke Rasmussen

This goal of this project is to develop support within StatWrap to generate customizable reproducibility checklists. The developer will use the metadata and user input collected by StatWrap to automatically generate checklists. This functionality will allow investigators to automatically generate a document indicating what practices they’ve followed to support reproducibility. Part of the project will involve surveying proposed reproducibility checklists and considering what to implement in StatWrap. This work will take a systematic approach to documenting reproducibility, much like PRISMA checklists for systematic reviews or CONSORT checklists for clinical trials.

The specific tasks of the project include:

Identify candidate reproducibility checklists to use as guides
Create the data structure for configuring reproducibility checklists
Display the reproducibility checklist in the user interface
Store responses and comments to the checklist as provided by the user
Generate a reproducibility checklist report from StatWrap

StatTag: Connecting statistical software to Microsoft Word

Mon, 22 Jan 2024 00:00:00 +0000

StatTag is a free, open-source software plug-in for conducting reproducible research. It facilitates the creation of dynamic documents using Microsoft Word documents and statistical software, such as Stata, SAS, R, and Python. Users can use StatTag to embed statistical output (estimates, tables and figures) into a Word document and then with one click individually or collectively update output with a call to the statistical program.

What makes StatTag different from other tools for creating dynamic documents is that it allows for statistical code to be edited directly from Microsoft Word. Using StatTag means that modifications to a dataset or analysis no longer require transcribing or re-copying results into a manuscript or table.

StatTag works by interpreting specially formatted comments (“tags”) within a code file. StatTag then reads the code file, executes the code through the corresponding language interpreter, formats the results, and inserts them into the Word document as a field.

There are versions of StatTag for both Microsoft Windows and macOS. Proposed projects here are specific to the Microsoft Windows version, which is developed in the C# programming language.

Additional Information:

Support Additional Programming Languages

Topics: reproducibility, statistics
Skills: C# and one of: MATLAB, Octave, SQL, Julia
Difficulty: Medium
Size: Medium or large (175 or 350 hours)
Mentor: Luke Rasmussen

Following the same structure used for other language support in StatTag, develop support for a new programming language (suggested languages are provided, but applicants can propose others). This will include:

Creating a Parser class to support StatTag-specific interpretation of results (e.g., identifying a line of code that is writing to a CSV file, then loading that CSV file)
Creating an Automation class that manages communication with the supported programming language’s interpreter. Python support uses a Jupyter kernel, and both SAS and Stata support invoke DLLs directly.
Integrating the language into the UI (e.g., allowing it to be a valid code file, adding the icon for the code file to the UI)
Additional setup/configuration as needed (e.g., SQL support would require secure configuration for connecting to the databse server).

Develop unit tests to demonstrate code is functioning. Create test scripts in the implemented language to exercise and demonstrate end-to-end execution.

Process Tags in Jupyter Notebooks

Topics: reproducibility, jupyter
Skills: C#, Jupyter Notebooks, Python
Difficulty: Medium
Size: Medium (175 hours)
Mentor: Luke Rasmussen

StatTag uses

StatTag currently has support for Python, and utilizes the Jupyter kernel to interact with Python. However, we currently do not fully support processing StatTag ’tags’ in a Jupyter notebook.

Following the same structure used for RMarkdown integration in StatTag, develop support for Jupyter Notebooks in StatTag. StatTag should be able to:

Take as input one or more Jupyter Notebooks
Confirm that the Jupyter Notebook uses Python
Identify StatTag formatted tags within the notebook
Pass relevant code to the Python processor already implemented in StatTag

In addition, develop unit tests to demonstrate code is functioning as intended. Create test Jupyter Notebooks to exercise and demonstrate end-to-end execution.