LEAP (0.2)

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Constructing Gene Co-Expression Networks for Single-Cell RNA-Sequencing Data Using Pseudotime Ordering.

http://cran.r-project.org/web/packages/LEAP

Advances in sequencing technology now allow researchers to capture the expression profiles of individual cells. Several algorithms have been developed to attempt to account for these effects by determining a cell's so-called `pseudotime', or relative biological state of transition. By applying these algorithms to single-cell sequencing data, we can sort cells into their pseudotemporal ordering based on gene expression. LEAP (Lag-based Expression Association for Pseudotime-series) then applies a time-series inspired lag-based correlation analysis to reveal linearly dependent genetic associations.

Maintainer: Alicia T. Specht
Author(s): Alicia T. Specht and Jun Li

License: GPL-2

Uses: ggplot2

Released almost 3 years ago.


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