Giter VIP home page Giter VIP logo

schist-notebooks's People

Contributors

dawe avatar

Stargazers

avatar avatar

Watchers

avatar avatar

schist-notebooks's Issues

HessianInversionWarning when performing the flat model analysis, described in the Cell_Marginals notebook

When I perform the analysis as described in Cell_Marginal notebook I get the following warning:
flat_results = [x.fit(method='lbfgs') for x in flat_model]

/home/morelli/anaconda3/envs/SCRNA/lib/python3.8/site-packages/statsmodels/base/model.py:547: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available

When this heppens, the analysis will not highlight any differentially expressed gene.
In order to overcome this problem, I've changed the code in the following way and I obtain some differentially expressed genes, but I don't know if the analysis is still correct :
flat_results = [x.fit() for x in flat_model]

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.