GithubHelp home page GithubHelp logo

limix / cellregmap Goto Github PK

View Code? Open in Web Editor NEW
20.0 3.0 3.0 11.43 MB

CellRegMap: A statistical framework for mapping context-specific regulatory variants using scRNA-seq

License: MIT License

Python 99.76% Dockerfile 0.24%
cellregmap scrna-seq eqtl sc-eqtl limix structlmm

cellregmap's Introduction

limix

Travis AppVeyor Documentation Forum

Genomic analyses require flexible models that can be adapted to the needs of the user.

Limix is a flexible and efficient linear mixed model library with interfaces to Python. It includes methods for

  • Single-variant association and interaction testing
  • Variance decompostion analysis with linear mixed models
  • Association and interaction set tests
  • Different utils for statistical analysis, basic i/o, and plotting.

We have an extensive documentation of the library. If you need further help or want to discuss anything related to limix, please, join our forum ๐Ÿ’ฌ and have a chat with us ๐Ÿ˜ƒ. In case you have found a bug, please, report it creating an issue.

Install

NOTE: We will be maintaining limix 2.0.x for a while, in case you find some missing feature in limix 3.0.x. If that is the case, please, type pip install "limix <3,>=2" in your terminal.

Installation is easy and works on macOS, Linux, and Windows:

pip install limix

If you already have Limix but want to upgrade it to the latest version:

pip install limix --upgrade

Interactive tutorials

Running tests

After installation, you can test it

python -c "import limix; limix.test()"

as long as you have pytest.

Authors

License

This project is licensed under the Apache License License.

cellregmap's People

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

cellregmap's Issues

input error help

Hi CellRegMap team,

I have been trying to implement the workflow in my dataset, and I have been running into problems with the inputs. I keep getting the same error with the covariates matrix "ValueError: There are non-finite values in the covariates matrix." Even if I use a simple interaction vector with the length of ncells
"
n_cells = phenotype.shape[1]
W = ones((n_cells, 1))
"
So that takes me to believe the problem is arising somewhere else. I have searched for non-finite values and I cannot find them in my data.

Here are my inputs, maybe you can spot an error I am overlooking?

Thanks in advance,
Marliette

`
print(y)
array([[-0.52708307],
[-0.52708307],
[-0.52708307],
...,
[-0.52708307],
[ 2.54097084],
[-0.52708307]])

print(y.shape)
(9226, 1)

print(W)
array([[0],
[0],
[0],
...,
[1],
[1],
[1]])

print(W.shape)
(9226, 1)

print(C_gauss)
array([[-1.22191296, 0.02241402, 1.08167398, ..., -0.37086214,
1.31544543, -1.22191296],
[-0.02132711, 1.11544898, 1.22535893, ..., -0.37086214,
1.31544543, -1.22191296],
[-0.72577874, 0.599198 , 0.48035595, ..., -0.37086214,
1.31544543, -1.22191296],
...,
[ 2.29981396, -2.31538738, 3.03765002, ..., -0.37086214,
-0.23817144, -0.20600968],
[ 2.40800678, -2.31144121, 2.11206554, ..., -0.37086214,
-0.23817144, -0.20600968],
[ 2.96421393, -2.27745124, 2.24930127, ..., -0.37086214,
-0.23817144, -0.20600968]])

print(C_gauss.shape)
(9226, 16)

print(GG)
array([[2.],
[2.],
[2.],
...,
[2.],
[2.],
[2.]], dtype=float32)

prit(GG.shape)
(9226, 1)

print(hK)
array([[0., 0., 0., ..., 0., 0., 0.],
[0., 0., 0., ..., 0., 0., 0.],
[0., 0., 0., ..., 0., 0., 0.],
...,
[0., 0., 0., ..., 0., 0., 0.],
[0., 0., 0., ..., 0., 0., 0.],
[0., 0., 0., ..., 0., 0., 0.]])

print(hK.shape)
(9226, 364)
`

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    ๐Ÿ–– 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. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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 โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.