causaldag
ims
causaldag | ims | |
---|---|---|
1 | 2 | |
133 | 827 | |
0.0% | 0.1% | |
0.0 | 9.4 | |
about 1 year ago | 2 days ago | |
JavaScript | JavaScript | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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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?
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
What are some alternatives?
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
android_ims
scTenifoldpy - A python package implements scTenifoldnet and scTenifoldknk
infernal-engine - A Tool to Build NodeJS and Web Based Expert Systems
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