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All Projects → quon-titative-biology → scAlign

quon-titative-biology / scAlign

Licence: GPL-3.0 license
A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions, batches

Programming Languages

r
7636 projects

Labels

scrna-seqsingle-cellsingle-cell-genomicsscrna-seq-analysishuman-cell-atlas

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scAlign

A deep learning-based tool for alignment and integration of single cell genomic data across multiple datasets, species, conditions and batches

Tutorials

First follow the install instructions below, at the bottom of the page, before following the tutorials.

Unsupervised alignment and projection of HSCs

Multiway alignment using all pairs method

Supervised/Semi-supervised alignment

Contributors

Chang Kim

Updates

(11/15/2021) Updated to Tensorflow 2. Now req. (Tensorflow >= 2.0)

(9/4/2019) Updated install instructions to include Tensorflow for R method.

(5/9/2019) Updated to version 1.0! Tutorials for multiple modes of operation now available.

R Package and Bioconductor

Bioconductor for now will only support the Linux version of scAlign.

The latest version of scAlign for all systems can always be found at github.

install.packages('devtools')
devtools::install_github(repo = 'quon-titative-biology/scAlign')
library(scAlign)

Package requirements

scAlign has three dependencies: Python 3, tensorflow (the R package), and tensorflow (the Python package). This is a guide to installing python and Tensorflow on different operating systems.

(Python)

All platforms:

  1. Download install binaries for Python 3 here

Alternative (On Windows):

  1. Download Python 3
  2. Make sure pip is included in the installation.

Alternative (On Ubuntu):

  1. sudo apt update
  2. sudo apt install python3-dev python3-pip

Alternative (On MacOS):

  1. /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
  2. export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
  3. brew update
  4. brew install python # Python 3

(Tensorflow)

In an R session:

install.packages('tensorflow') #install the tensorflow R package (that sits on top of the TensorFlow python package)
library(tensorflow)
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