cookiecutter-snakemake-workflow
pypsa-eur
| cookiecutter-snakemake-workflow | pypsa-eur | |
|---|---|---|
| 1 | 3 | |
| 55 | 288 | |
| - | 4.5% | |
| 1.8 | 9.9 | |
| over 2 years ago | 7 days ago | |
| Python | Python | |
| MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cookiecutter-snakemake-workflow
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Development notes in Snakemake workflows
I currently use cookiecutter to start new Snakemake repositories (projects) because it's really comfortable and guarantees that I follow an organized and recommended directory structure. However, I have a tendency to make notes during development. Maybe I made some decision based on something I learned in biostars or reddit and I want to remember that, or I start by outlining my workflow steps in written form. So far I've used both the README file and the Snakemake file (comments) to do that, but I'm wondering if anyone has a suggestion for how to fit development notes within a Snakemake project.
pypsa-eur
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U.S. can get to 100% clean energy with wind, water, solar and zero nuclear, Stanford professor says
It's more predictable than you seem to think, especially at large scale. Grid modelers use sophisticated computer models (like PyPSA) to find the cheapest low-carbon technological mix, based on historical consumption and weather data. You might like to read Synergies of sector coupling for instance, they describe how the variability of wind and solar is handled.
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Bill Gates: Nuclear power will 'absolutely' be politically acceptable again — it's safer than oil, coal, natural gas
Well, some very knowledgeable people have done the math and they are pretty sure about their conclusions :) The grid is a very complicated beast, and it's nearly impossible to visualize some stuff without running a sophisticated computer model (like this one). What they don't cover is stuff like political issues, mismanagement etc, and that's certainly worth a discussion.
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The Empire State Building and its related buildings are now powered by wind - The skyscraper and 13 other office buildings owned by the same company were powered solely by wind.
Or you could go study some of their models and note that they use real weather and consumption data.
What are some alternatives?
cookiecutter-data-science - A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
atlas - ATLAS - Three commands to start analyzing your metagenome data
metaGEM - :gem: An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data
GermlineMutationCalling - An adaptable Snakemake workflow which uses GATKs best practice recommendations to perform germline mutation calling starting with BAM files
FastAPI-template - Feature rich robust FastAPI template.
RNA-seq-analysis - RNAseq analysis notes from Ming Tang
hecatomb - hecatomb is a virome analysis pipeline for analysis of Illumina sequence data
PyPSA - PyPSA: Python for Power System Analysis
snakemake - This is the development home of the workflow management system Snakemake. For general information, see
pypsa-earth - PyPSA-Earth: A flexible Python-based open optimisation model to study energy system futures around the world.