ddClone – Joint Clustering of Single Cell and Bulk Data

ddClone

:: DESCRIPTION

A statistical framework leveraging data obtained from both single cell and bulk sequencing strategies. The ddClone is predicated on the notion that single cell sequencing data will inform and improve clustering of allele fractions derived from bulk sequencing data in a joint statistical model.

::DEVELOPER

Shah Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • R

:: DOWNLOAD

ddClone

:: MORE INFORMATION

Citation

Genome Biol. 2017 Mar 1;18(1):44. doi: 10.1186/s13059-017-1169-3.
ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data.
Salehi S, Steif A, Roth A, Aparicio S, Bouchard-Côté A, Shah SP

CellScape 0.99.3 – Visualization tool for integrating single Cell Phylogeny

CellScape 0.99.3

:: DESCRIPTION

CellScape is a visualization tool for integrating single cell phylogeny with genomic content to clearly display evolutionary progression and tumour heterogeneity.

::DEVELOPER

Shah Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • R

:: DOWNLOAD

CellScape

:: MORE INFORMATION

VASC – Variational Autoencoder for Single Cell RNA-seq datasets

VASC

:: DESCRIPTION

VASC (deep Variational Autoencoder for SCRNA-seq data) is a deep multi-layer generative model, for the dimension reduction and visualization. It can do nonlinear hierarchical feature representations and model the dropout events of scRNA-seq data. Tested on more than twenty datasets, VASC show better performances in most cases and higher stability compared with several dimension reduction methods. VASC successfully re-establishes the embryo pre-implantation cell lineage and its associated genes based on the 2D representation of a large-scale scRNA-seq from human embryos.

::DEVELOPER

Bioinformatics & Intelligent Information Processing Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python 3.5+
  • numpy 1.12.1
  • h5py 2.7.0
  • sklearn 0.18.1
  • tensorflow 1.1.0
  • keras 2.0.6

:: DOWNLOAD

VASC

:: MORE INFORMATION

Citation

VASC: dimension reduction and visualization of single cell RNA sequencing data by deep variational autoencoder.
Genomics, Proteomics & Bioinformatics 2018, 16(5):320-331.
Dongfang Wang, Jin Gu

TSCAN 1.7.0 – Pseudo-time Reconstruction and Evaluation in Single-cell RNA-seq Analysis

TSCAN 1.7.0

:: DESCRIPTION

TSCAN (Tools for Single-Cell ANalysis) is a software tool developed to better support in silico pseudo-Time reconstruction in Single-Cell RNA-seq ANalysis.

::DEVELOPER

Zhicheng Ji

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

 TSCAN

:: MORE INFORMATION

Citation

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.
Ji Z, Ji H.
Nucleic Acids Res. 2016 May 13. pii: gkw430.

OEFinder 0.0.2 – Identify Ordering Effect Genes in Single Cell RNA-seq data

OEFinder 0.0.2

:: DESCRIPTION

OEFinder is a user interface to identify and visualize ordering effects in single-cell RNA-seq data.

::DEVELOPER

Ning Leng

:: SCREENSHOTS

OEFinder

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

 OEFinder

:: MORE INFORMATION

Citation

OEFinder: A user interface to identify and visualize ordering effects in single-cell RNA-seq data.
Leng N, Choi J, Chu LF, Thomson JA, Kendziorski C, Stewart R.
Bioinformatics. 2016 Jan 6. pii: btw004.

pcaReduce 1.0 – Hierarchical Clustering of Single Cell Transcriptional Profiles

pcaReduce 1.0

:: DESCRIPTION

pcaReduce is a novel agglomerative clustering method to generate a cell state hierarchy where each cluster branch is associated with a principal component of variation that can be used to differentiate two cell states.

::DEVELOPER

pcaReduce team

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

 pcaReduce

:: MORE INFORMATION

Citation

pcaReduce: hierarchical clustering of single cell transcriptional profiles.
Žurauskienė J, Yau C.
BMC Bioinformatics. 2016 Mar 22;17(1):140. doi: 10.1186/s12859-016-0984-y.

SingleCellAssay 1.0.1 – Infrastructure and Tools for Single Cell Assay Analysis

SingleCellAssay 1.0.1

:: DESCRIPTION

SingleCellAssay is a suit of tools and methods for analysis of single cell assay data in R

::DEVELOPER

RGLAB

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/MacOsX
  • R

:: DOWNLOAD

 SingleCellAssay

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Feb 15;29(4):461-7. doi: 10.1093/bioinformatics/bts714. Epub 2012 Dec 24.
Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments.
McDavid A1, Finak G, Chattopadyay PK, Dominguez M, Lamoreaux L, Ma SS, Roederer M, Gottardo R.

SPAdes 3.6.2 – Single-cell Genome Assembler

SPAdes 3.6.2

:: DESCRIPTION

SPAdes (St. Petersburg genome assembler) is intended for both standard isolates and single-cell MDA bacteria assemblies.

::DEVELOPER

Algorithmic Biology Lab at St. Petersburg Academic University of the Russian Academy of Sciences

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  MacOsX
  • Python

:: DOWNLOAD

 SPAdes

:: MORE INFORMATION

Citation

hybridSPAdes: an algorithm for hybrid assembly of short and long reads.
Antipov D, Korobeynikov A, McLean JS, Pevzner PA.
Bioinformatics. 2015 Nov 20. pii: btv688

Anton Bankevich,et al.
SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing.
Journal of Computational Biology 19(5) (2012), 455-477. doi:10.1089/cmb.2012.0021

GRM 0.2.1 – Single Cell RNA-seq De-noise Tools

GRM 0.2.1

:: DESCRIPTION

GRM is a powerful but simple method to remove technical noise and explicitly compute the true gene expression levels based on spike-in ERCC molecules.

::DEVELOPER

Wei Wang’s group

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

 GRM

:: MORE INFORMATION

Citation

Normalization and noise reduction for single cell RNA-seq experiments.
Ding B, Zheng L, Zhu Y, Li N, Jia H, Ai R, Wildberg A, Wang W.
Bioinformatics. 2015 Feb 24. pii: btv122.

FiloDetect – Detect & Quantify Filopodia in Single-cell Fluorescence Confocal Microscopy Images

FiloDetect

:: DESCRIPTION

FiloDetect is an image analysis program for detecting and quantifying filopodia in single-cell fluorescence confocal microscopy images.

::DEVELOPER

Perkins Lab at the OHRI

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / MacOsX /Windows
  •  MatLab

:: DOWNLOAD

 FiloDetect

:: MORE INFORMATION

Citation

S. Nilufar, A. A. Morrow, J. M. Lee, T. J. Perkins
FiloDetect: Automatic Detection of Filopodia from Fluorescence Microscopy Images
BMC Syst Biol. 2013 Jul 23;7:66. doi: 10.1186/1752-0509-7-66.