ims
causaldag
ims | causaldag | |
---|---|---|
2 | 1 | |
827 | 133 | |
0.2% | 0.0% | |
9.4 | 0.0 | |
1 day ago | about 1 year ago | |
JavaScript | JavaScript | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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ims
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Introduction to Modern Statistics
Seems to be mostly Creative Commons BY-SA 3.0 but there's a lot of "yes, but" language in that file: https://github.com/OpenIntroStat/ims/blob/main/LICENSE.md
causaldag
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Any methods or tools for virtual gene knock-out in single cell RNA seq data?
I am interested in finding out bioinformatically, a causal relationship between an upstream gene (Notch2) and a transcription factor downstream. Is there any other tool other than scTenifoldpy, to perform a virtual knock-down of genes of interest and see which other genes are affected? Is there also any other tool than causaldag that can help infer causal relationships between gene expressions?
What are some alternatives?
android_ims
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
infernal-engine - A Tool to Build NodeJS and Web Based Expert Systems
scTenifoldpy - A python package implements scTenifoldnet and scTenifoldknk
stat-cookbook - :orange_book: The probability and statistics cookbook
doubango - Doubango VoIP framework
tests-as-linear - Common statistical tests are linear models (or: how to teach stats)
jasp-desktop - JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS
statistical-rethinking - A repository for working through the Bayesian statistics book "Statistical Rethinking" by Richard McElreath.
textbook - The textbook Computational and Inferential Thinking: The Foundations of Data Science