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Claude AI Context for MacCoss Lab Website

This file provides context for Claude AI when working with this repository.

Project Overview

This is the MacCoss Lab website at the University of Washington, hosted on GitHub Pages at:

The lab focuses on mass spectrometry-based proteomics research, developing methods and software for protein analysis.

Technology Stack

  • Static Site Generator: Jekyll with Minima theme
  • Hosting: GitHub Pages
  • Styling: SCSS (assets/main.scss)

Key Files and Directories

_config.yml              # Jekyll configuration
_layouts/                # Custom HTML layouts
_posts/                  # News/blog posts (for RSS feed)
assets/
  main.scss              # Custom styling
  images/                # All images (logos, instruments, people, plots)
pages/                   # Main site content pages
scripts/
  fetch_publications.py         # Automated publication fetcher
  fetch_skyline_events.py       # Automated Skyline events/webinars fetcher
  fetch_educational_materials.py # Automated educational materials fetcher

Automated Publication System

The site has an automated system (scripts/fetch_publications.py) that:

  1. Fetches Google Scholar metrics (total citations, h-index, most cited paper)
  2. Fetches ALL publications from PubMed (searches for MacCoss MJ as author)
  3. Generates a metrics plot (publications/citations per year)
  4. Regenerates pages/publications.md with year-based navigation sidebar

Year-Based Navigation

Publications are displayed with a sidebar showing all years. Clicking a year shows only that year's publications. The layout uses:

  • .publications-container - flexbox layout with sidebar
  • .year-navigation - sticky sidebar with year buttons
  • .year-content - content divs for each year (only one visible at a time)

Publication Sources

  • All publications are fetched from PubMed (including preprints)
  • This ensures the sidebar counts match the Publications per Year plot

Running the Script

The script must be run manually from a local machine (Google Scholar blocks CI environments).

First-time setup:

python3 -m venv .venv
source .venv/bin/activate
pip install requests beautifulsoup4 matplotlib numpy

To update publications:

source .venv/bin/activate
python3 scripts/fetch_publications.py
git add -A && git commit -m "Update publications" && git push

Automated Skyline Events System

The site has an automated system (scripts/fetch_skyline_events.py) that:

  1. Fetches events from https://skyline.ms/home/software/Skyline/events/project-begin.view
  2. Fetches webinars from https://skyline.ms/home/software/Skyline/wiki-page.view?name=webinars
  3. Updates pages/resources.md Support & Training tab with year-based navigation

Year-Based Navigation for Events

Past events are displayed with a sidebar showing all years (2013-present). Clicking a year shows only that year's events. The layout uses:

  • .events-container - flexbox layout with sidebar
  • .event-year-navigation - sticky sidebar with year buttons
  • .event-year-content-area - content divs for each year

Running the Script

To update Skyline events:

source .venv/bin/activate
python3 scripts/fetch_skyline_events.py
git add -A && git commit -m "Update Skyline events" && git push

Automated Educational Materials System

The site has an automated system (scripts/fetch_educational_materials.py) that:

  1. Uses curated Skyline tutorials list (27 tutorials across 6 categories)
  2. Fetches UWPR online calculators from https://proteomicsresource.washington.edu/protocols06/
  3. Updates pages/resources.md Educational Materials tab

Data Sources

Running the Script

To update educational materials:

source .venv/bin/activate
python3 scripts/fetch_educational_materials.py
git add -A && git commit -m "Update educational materials" && git push

Automated Datasets System

The site has an automated system (scripts/fetch_datasets.py) that:

  1. Fetches datasets from Panorama Public API using LabKey query-selectRows API with authentication
  2. Falls back to curated datasets list if API key is not available
  3. Updates pages/resources.md Datasets tab with year-based organization

API Authentication

The Panorama Public API requires authentication to query across all subfolders. The script looks for an API key in:

  1. PANORAMA_API_KEY environment variable
  2. .env file in the project root (format: PANORAMA_API_KEY=your_key_here)
  3. ~/.panorama_credentials file (just the key)

Important: API key files (.env, .panorama_credentials) are in .gitignore to prevent accidental commits.

Data Source

Dataset Organization

  • With API: Datasets organized by year (2025, 2024, etc.)
  • Fallback: Datasets organized by category (Instrumentation, Method Development, etc.)

Running the Script

To update datasets:

source .venv/bin/activate
python3 scripts/fetch_datasets.py
git add -A && git commit -m "Update datasets" && git push

Content Guidelines

Adding Publications

Publications are managed automatically via the script. Manual additions should follow this format:

**Paper Title**
Author1, Author2, MacCoss MJ, ...
*Journal Name* Year Month;Volume(Issue):Pages
[PubMed](https://pubmed.ncbi.nlm.nih.gov/PMID/) | [DOI](https://doi.org/...)

Adding News Posts

Create files in _posts/ with format YYYY-MM-DD-title.md:

---
layout: post
title: "Post Title"
date: YYYY-MM-DD
categories: [category1, category2]
---
Post content here...

Image Organization

  • assets/images/logos/ - Software and lab logos
  • assets/images/instruments/ - Mass spectrometer photos
  • assets/images/people/ - Lab member headshots
  • assets/images/publication-metrics.png - Auto-generated plot

Common Tasks

Update publications

source .venv/bin/activate
python3 scripts/fetch_publications.py
git add -A && git commit -m "Update publications" && git push

Update Skyline events

source .venv/bin/activate
python3 scripts/fetch_skyline_events.py
git add -A && git commit -m "Update Skyline events" && git push

Update educational materials

source .venv/bin/activate
python3 scripts/fetch_educational_materials.py
git add -A && git commit -m "Update educational materials" && git push

Update datasets

source .venv/bin/activate
python3 scripts/fetch_datasets.py
git add -A && git commit -m "Update datasets" && git push

Test site locally

bundle exec jekyll serve

Check for preprints/corrigenda

grep -i "biorxiv\|arxiv\|corrigendum" pages/publications.md

Dependencies for Scripts

Python packages required:

  • requests - HTTP requests
  • beautifulsoup4 - HTML parsing for Google Scholar
  • matplotlib - Plot generation
  • numpy - Numerical support

Important Notes

  1. Google Scholar scraping: May occasionally fail if Google blocks requests. The script handles this gracefully and continues with other updates.

  2. PubMed API: Uses NCBI E-utilities (no API key required for low-volume requests).

  3. Publication metrics format: Numbers should NOT have > or + symbols since they're updated weekly.

  4. Tab navigation: Multiple pages use JavaScript-based tabs (Resources, People, Funding).

  5. Email obfuscation: All emails use [at] and [dot] format to reduce spam.

Lab Information

  • PI: Michael MacCoss
  • Institution: University of Washington, Department of Genome Sciences
  • Research focus: Quantitative proteomics, mass spectrometry methods, Skyline software development
  • Key software: Skyline, Panorama, Encyclopedia, Limelight

When Making Changes

  1. Test locally with bundle exec jekyll serve when possible
  2. Check for broken image paths after moving files
  3. Maintain consistent formatting in publication entries
  4. Ensure new images are optimized for web
  5. Run the publication script to verify it still works after changes