SNN-Cliq 1.0 – Clustering method for High Dimensional Dataset

SNN-Cliq 1.0

:: DESCRIPTION

SNN-Cliq is a clustering method designed for high dimensional gene expression data, e.g. single-cell transcriptome data. This method can effectively cluster individual cells based on their transcriptomes, producing clustering outputs highly in accordance with the cell type origins. SNN-Cliq utilizes the concept of shared nearest neighbor (SNN) to define similarities between data points (cells) and achieve clustering by a graph theory-based algorithm.

::DEVELOPER

Chen Xu in Dr. Su’s lab at the University of North Carolina at Charlotte.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /Windows
  • R / MatLab/ Python

:: DOWNLOAD

 SNN-Cliq

:: MORE INFORMATION

Citation

Identification of cell types from single-cell transcriptomes using a novel clustering method.
Xu C, Su Z.
Bioinformatics. 2015 Feb 11. pii: btv088.

HiDimViewer – Visualization tool for High-dimensional Datasets

HiDimViewer

:: DESCRIPTION

HiDimViewer is a visualization tool we are developing for high-dimensional datasets. It is designed to be used as an interactive data exploration tool to aid scientists in selecting and observing clusters in high-dimensional data.

::DEVELOPER

the UNC Computational Genetics Working Group

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 HiDimViewer

:: MORE INFORMATION