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Principal Developemental Trajectories Estimation

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Overview

This repository is in support of the publication Pellin, D. et al. "A comprehensive single cell transcriptional landscape of human hematopoietic progenitors." Nature communications (2019) and consists of an R implementation of the structure-aware algorithm aimed to at revealing and consolidating continuous, low-dimensional and high- density structures in the underlying higher-dimensional data, while ignoring noise and outliers. The theory, proof of convergence to the exact underlying data manifolds (under Gaussian noise assumption) and a deep investigation of its performance under different scenario can be found in Wu, Shihao, et al. [Wu, Shihao, et al. "Structure-aware Data Consolidation." IEEE transactions on pattern analysis and machine intelligence (2017)]

Repo Contents

System Requirements

Hardware Requirements

The script requires only a standard computer with enough RAM (>4Gb) to analyze a dataset with 10K obs. in a 2-dimensional space. The runtimes on provided datsets is approximately 4 minutes.

Software Requirements

The script had been developed and tested on R version 3.4.x

Package dependencies

Users should install the following packages prior to run PrincDevelTraj.R, from an R terminal:

install.packages(c('RANN', 'parallel'))

Reproducibility

To reproduce results published in our paper set parameters with the following values:

  • coordinates_sorted_HSPC_dataset.txt -> radius= 0.05; mu= 0.3;
  • coordinates_CD34_CD164_dataset.txt -> radius= 0.02; mu= 0.3;

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