README.md

In tinglab/redPATH: Reconstructing the pseudo development time of cell lineages in single cell RNA-Seq data and applications in cancer.

redPATH

redPATH reconstructs the pseudo development time of cell lineages in single-cell RNA-seq data. It formulates the problem of pseudo temporal ordering into a Hamiltonian path problem and attempts to recover the pseudo development time in single-cell RNA-seq datasets. We provide a comprehensive analysis software tool with robust performance.

Overview

## Table of content - [Installation](#installation) - [Required Packages](#required_packages) - [Install](#install) - [Example Usage](#example_usage) - [Preprocessing](#preprocessing) - [redPATH pseudotime](#redpath_pseudotime) - [Biological Analysis](#bio_analysis) - [Citation](#cite) - [Maintenance](#maintenance) ## Installation ### - Required Packages car, combinat, doParallel, dplyr, energy, ggplot2, GOsummaries, gplots, MASS, mclust, minerva, plotly, Rcpp, RcppArmadillo, scater ### - Install After downloading the package, please extract and rename the folder to "redPATH" wzxhzdk:0 ## Example Usage: ### - Preprocessing Assuming your input data is a m genes (rows) by n cells (cols) matrix. Here, a neural stem cell (145 cells) dataset from 2015 (1) is used as an example analysis and a diseased example (MGH107 - 252 cells) dataset is also provided from 2017 (2). wzxhzdk:1 An optional function is also available to identify the G0-like cells: wzxhzdk:2 ### - redPATH pseudotime wzxhzdk:3 ### - Biological Analysis #### 1. Discovery of potential marker genes wzxhzdk:4 #### 2. Heatmap & Gene Ontology Analysis ##### - Producing heatmaps wzxhzdk:5 ##### - Gene Ontology plots wzxhzdk:6 #### 3. 3D Cell proliferation and differentiation plots: ##### - 3D plot with cell type labels and cell cycle stages wzxhzdk:7 ##### - Plot with marker gene wzxhzdk:8 ## Citation & References This work is currently under submission. Reconstructing the pseudo development time of cell lineages in single-cell RNA-seq data and applications in cancer. References: ###### 1. Llorens-Bobadilla, E., Zhao, S., Baser, A., Saiz-Castro, G., Zwadlo, K. and Martin-Villalba, A. (2015) Single-Cell Transcriptomics Reveals a Population of Dormant Neural Stem Cells that Become Activated upon Brain Injury. Cell Stem Cell, 17, 329-340. ###### 2. Venteicher, A.S., Tirosh, I., Hebert, C., Yizhak, K., Neftel, C., Filbin, M.G., Hovestadt, V., Escalante, L.E., Shaw, M.L., Rodman, C. et al. (2017) Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science, 355. ## Maintenance If there's any questions / problems regarding redPATH, please feel free to contact Ken Xie - [e-mail]. Thank you!

tinglab/redPATH documentation built on May 31, 2019, 10:37 a.m.