soedinglab/merlot

Name: merlot

Owner: Söding Lab

Description: Reconstruct the lineage topology of a scRNA-seq differentiation daatset.

Created: 2017-06-29 15:05:22.0

Updated: 2018-02-05 18:22:13.0

Pushed: 2018-02-05 14:26:44.0

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Size: 10129

Language: R

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README

MERLot: A MEthod for Reconstructing Lineage tree Topologies using scRNA-seq data

MERLot is a tool that can reconstruct the lineage tree topology that explains the emergence of different cell types from a progenitor population. MERLot is an R package than can reconstruct complex lineage tree topologies using coordinates for cells in a given manifold(like diffusion maps) as input.

Get ready

1) Python Dependencies:

MERLoT consists of 1 part written in Python, which is distributed with the R package for which the following packages need to be installed. Take into account that MERLoT uses python 3.

• scipy
• pandas
• python3-tk
• numpy
• csgraph_mod (modified version of csgraph) which you can install from here: https://github.com/soedinglab/csgraph_mod

NOTE: In case you don?t have a standard python3 installation, e.g you installed it using anaconda, when using the package you will need to set the location of your working python3 binary in the python_url variable in the ScaffoldTree() function. By default it is set to ?/usr/bin/python3? (See the Vignette Section, ScaffoldTree() function, for more information).

2) R Dependencies:

MERLoT depends on certain R packages in order to work properly. Most of the packages can be installed either via CRAN (with the install.packages() function) or via Bioconductor.

• car
• rgl
• rpgraph
• igraph
• fields

The Destiny package for creating diffusion maps was one of the dinmensionality reduction techniques we used in order to reconstruct lineage tree topologies in a low dimensional manifold.

The destiny package as well as how to install it and use it can be found here

Optional packages:

• energy (needed for finding differentially expressed genes)
• VGAM

Rpgraph can be installed following the instructions from the developer's site.

The steps can be summarized in: install.packages(pkgs = "rJava", repos="http://rforge.net", type = 'source')

For rJava you have to have Java installed in your system. You can install default-jre, open jdk

install.packages("devtools") library(devtools) install.packages(c("bigpca", "irlba", "nsprcomp", "plotly","fields", "igraph", "rgl", "tictoc"))

3) Download

Download the merlot file.

4) Install MERLoT

Install from source:

install.packages("/url_in_your_computer/merlot-master.zip", types="source", repos = NULL)

Install from github:

library(devtools)

install_github("soedinglab/merlot")