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Top 23 reproducible-research Open-Source Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Sacred
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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ITK
Insight Toolkit (ITK) -- Official Repository. ITK builds on a proven, spatially-oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
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drake
An R-focused pipeline toolkit for reproducibility and high-performance computing (by ropensci)
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gpu-jupyter
GPU-Jupyter: Leverage the flexibility of Jupyterlab through the power of your NVIDIA GPU to run your code from Tensorflow and Pytorch in collaborative notebooks on the GPU.
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papaja
papaja (Preparing APA Journal Articles) is an R package that provides document formats to produce complete APA manuscripts from RMarkdown-files (PDF and Word documents) and helper functions that facilitate reporting statistics, tables, and plots.
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sarek
Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing
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huxtable
An R package to create styled tables in multiple output formats, with a friendly, modern interface.
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trackdown
R package for collaborative writing and editing of R Markdown (or Sweave) documents in Google Docs.
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htm.core
Actively developed Hierarchical Temporal Memory (HTM) community fork (continuation) of NuPIC. Implementation for C++ and Python
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: Sacred VS cascade - a user suggested alternative | libhunt.com/r/sacred | 2023-12-05
> It's been a while since you can rerun/resume Nextflow pipelines
Yes, you can resume, but you need your whole upstream DAG to be present. Snakemake can rerun a job when only the dependencies of that job are present, which allows to neatly manage the disk usage, or archive an intermediate state of a project and rerun things from there.
> and yes, you can have dry runs in Nextflow
You have stubs, which really isn't the same thing.
> I have no idea what you're referring to with the 'arbitrary limit of 1000 parallel jobs' though
I was referring to this issue: https://github.com/nextflow-io/nextflow/issues/1871. Except, the discussion doesn't give the issue a full justice. Nextflow spans each job in a separate thread, and when it tries to span 1000+ condor jobs it die with a cryptic error message. The option of -Dnxf.pool.type=sync and -Dnxf.pool.maxThreads=N prevents the ability to resume and attempts to rerun the pipeline.
> As for deleting temporary files, there are features that allow you to do a few things related to that, and other features being implemented.
There are some hacks for this - but nothing I would feel safe to integrate into a production tool. They are implementing something - you're right - and it's been the case for several years now, so we'll see.
Snakemake has all that out of the box.
Project mention: GitHub - JunoLab/Weave.jl: Scientific reports/literate programming for Julia | /r/LitProg | 2023-05-31
Project mention: What type of table is this, and is there a way to do this in R? | /r/RStudio | 2023-12-06As for styling, I highly recommend the huxtable package. You can style rows, columns, and individual cells however you want. It uses dplyr pipelining, if you’re familiar with that, so it’s super intuitive to use too.
reproducible-research related posts
- What type of table is this, and is there a way to do this in R?
- GitHub - JunoLab/Weave.jl: Scientific reports/literate programming for Julia
- Is there anything like funflow for rust?
- Literate DevOps
- Any place to do collaboratie writing in the new quarto format? if not, what's the best place/way to do it in rmarkdown you think?
- Researchers From INRIA France Propose ‘Pythae’: An Open-Source Python Library Unifying Common And State-of-the-Art Generative AutoEncoder (GAE) Implementations
- [P] Pythae - Unifying generative autoencoder implementations in Python
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A note from our sponsor - WorkOS
workos.com | 25 Apr 2024
Index
What are some of the best open-source reproducible-research projects? This list will help you:
Project | Stars | |
---|---|---|
1 | metaflow | 7,586 |
2 | PyTorch-VAE | 5,989 |
3 | Sacred | 4,157 |
4 | nextflow | 2,538 |
5 | fma | 2,108 |
6 | benchmark_VAE | 1,680 |
7 | EvalAI | 1,677 |
8 | ITK | 1,339 |
9 | drake | 1,330 |
10 | torch-fidelity | 870 |
11 | targets | 866 |
12 | Weave.jl | 814 |
13 | disentangling-vae | 753 |
14 | gpu-jupyter | 661 |
15 | papaja | 626 |
16 | codebraid | 361 |
17 | funflow | 360 |
18 | sarek | 333 |
19 | huxtable | 311 |
20 | trackdown | 209 |
21 | example-get-started | 167 |
22 | shournal | 159 |
23 | htm.core | 144 |
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