D-CE

D-CE (Developmental Coalescent Embedding): An effective landmark free and model free de novo 3D reconstruction method for single cell analysis.

Introduction

De novo reconstruction of single cell 3D spatial tissue localization is hitherto landmark based so far, and de novo spatial reconstruction is a compelling computational open problem.Theoretically, cells adjacent in space have similar gene expression patterns, for example, the anterior and posterior determination during embryonic development.We rely merely on the spatial information encoded in the gene expression patterns, and we find that D-CE of cell-cell association DST-transcriptomic networks can reliably reconstructs the single cell samples 3D spatial tissue distribution.

If you find D-CE useful, please give us a star at github and cite our paper.

Folders description

• visualization.m Matlab codes to visualize the D-CE reconstructed structure of E7.5 Geo-seq;

• expE7.5allsample.txt An example of input data from Geo-seq gene E7.5 sample, with genes on the columns and samples on the rows, there is no need for rownames and colnames;

• Info.mat Sample annotation information of the example input data, including layer, germ layer of E7.5 and color for visualization;

• D-CE_windows Windows version of the main function of spatial reconstruction, includes the codes for expression matrix normalization, pair-wise distance calculation and dimensionality reduction based on coalescent embedding and integrated into one function;
   -spatial_reconstruct.exe
   -readme file

• D-CE_linux Linux version of the main function of spatial reconstruction, includes the codes for expression matrix normalization, pair-wise distance calculation and dimensionality reduction based on coalescent embedding and integrated into one function;
   -spatial_reconstruct
   -spatial_reconstruct.sh (shell script for temporarily setting environment variables and executing the application)
   -readme file

• mapping and EOC the function for one to one mapping of samples to the spatial locations and EOC spatial marker selection;
   -EOC_MarkerGeneSelection.R R code for marker gene selection
   -TPM.txt, Reconstructed_Coordinate.txt expression matrix and spatial coodinates matrix, as the input of marker gene selection function
   -mapping.py python function for mapping of samples to the spatial locations
   -coordreconstruct.txt, geometry.txt D-CE reconstructed coordinates and spatial coodinates matrix, as the input of mapping function

Requirements

MATLAB(>=R2017b).

MATLAB Runtime please verify the MATLAB Runtime is installed and ensure you have installed version 9.2 (R2017a) for windows or version 9.3 (R2017b) for linux. If not, do as follow:
 (1) enter 'mcrinstaller' at MATLAB prompt. The MCRINSTALLER command displays the location of the MATLAB Runtime installer
 (2) run the MATLAB Runtime installer. Or download right version of the MATLAB Runtime from the MathWorks Web site
 http://www.mathworks.com/products/compiler/mcr/index.html

MatlabBGL library The support functions of the MatlabBGL library can be downloaded at: http://mathworks.com/matlabcentral/fileexchange/10922-matlabbgl

PROPACK library The support functions of the PROPACK library can be downloaded at: https://github.com/mavenlin/PropackMatlab4Windows https://github.com/epfl-lts2/unlocbox/tree/master/test_bench/private

Usage

For Windows User

To run the demo, just double click the spatial_reconstruct.exe, then type the path of the expression data 'expE7.5allsample.txt', and 'Y' or 'N', which means you will or won't use CSI matrix in the 3D reconstruction. Wait about 10 secounds for the output file '3Dcoordinates.txt', which is the reconstructed 3D coordinates of the example sample. Finally, run visualization.m in MATLAB for visualization.

For Linux User

Type the following command at Linux or Mac command prompt:

git clone https://github.com/JackieHanLab/D-CE
cd D-CE/D-CE_linux
chomd a+x spatial_reconstruct.sh
chomd a+x spatial_reconstruct
./spatial_reconstruct.sh <mcr_directory>  

<mcr_directory> is the directory where version MATLAB Runtime installed or the directory where MATLAB is installed on the machine. For example, If you have MATLAB Runtime installed in /mathworks/home/application/v93, run the shell script as:

./spatial_reconstruct.sh /mathworks/home/application/v93

If you have MATLAB installed in /mathworks/devel/application/matlab, run the shell script as:

./spatial_reconstruct.sh /mathworks/devel/application/matlab

Then, similar to Windows version, just type the path of matrix and 'Y' or 'N' to run the 3D reconstruction.

To run the demo for mapping of samples to spatial coordinates, type the following command:

python mapping.py -c [path of reconstructed coordinates] -t [path of spatial coordinates of locations]

Reference

Muscoloni, A., Thomas, J. M., Ciucci, S., Bianconi, G. & Cannistraci, C. V. Machine learning meets complex networks via coalescent embedding in the hyperbolic space. Nat Commun 8, 1615, doi:10.1038/s41467-017-01825-5 (2017).

Peng, G. et al. Molecular architecture of lineage allocation and tissue organization in early mouse embryo. Nature 572, 528-532, doi:10.1038/s41586-019-1469-8 (2019).

Nitzan, M., Karaiskos, N., Friedman, N. & Rajewsky, N. Gene expression cartography. Nature 576, 132-137, doi:10.1038/s41586-019-1773-3 (2019).

Contact

For any problems, please contact:
Yuxuan Zhao: zhaoyuxuan2017@pku.edu.cn
Jing-Dong J. Han: jackie.han@pku.edu.cn