BCseq – Accurate Single Cell RNA-seq Quantification with Bias Correction

BCseq

:: DESCRIPTION

BCseq (bias-corrected sequencing analysis) is a software tool to quantify gene expression from scRNA-seq.

:: DEVELOPER

Liang Chen’s Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • R

:: DOWNLOAD

BCseq

:: MORE INFORMATION

Citation:

BCseq: accurate single cell RNA-seq quantification with bias correction.
Chen L, Zheng S.
Nucleic Acids Res. 2018 Aug 21;46(14):e82. doi: 10.1093/nar/gky308.

SINC – Scale-invariant Deep Neural-network Classifier for Bulk and Single-Cell RNA-seq.

SINC

:: DESCRIPTION

SINC is a deep-neural-network Classifier for Bulk and Single-Cell RNA-seq.

::DEVELOPER

Jun Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX/  Linux / WIndows
  • Python

SINC

:: MORE INFORMATION

Citation

Bioinformatics, 36 (6), 1779-1784 2020 Mar 1
SINC: A Scale-Invariant Deep-Neural-Network Classifier for Bulk and Single-Cell RNA-seq Data
Chuanqi Wang , Jun Li

DWLS – Cell-type Deconvolution using Single-cell RNA-sequencing data

DWLS

:: DESCRIPTION

DWLS (Dampened weighted least squares) is an estimation method for gene expression deconvolution, in which the cell-type composition of a bulk RNA-seq data set is computationally inferred.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R

:: DOWNLOAD

DWLS

:: MORE INFORMATION

Citation

Tsoucas D, Dong R, Chen H, Zhu Q, Guo G, Yuan GC.
Accurate estimation of cell-type composition from gene expression data.
Nature Communications. 10 (1), 2975 2019 Jul 5

RESCUE v1.0.0 – Imputing Dropouts in Single-cell RNA-sequencing data

RESCUE v1.0.0

:: DESCRIPTION

RESCUE is a computational method to mitigate the dropout problem by imputing gene expression levels using information from other cells with similar patterns.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python
  • R

:: DOWNLOAD

RESCUE

:: MORE INFORMATION

Citation

BMC Bioinformatics, 20 (1), 388 2019 Jul 12
RESCUE: Imputing Dropout Events in Single-Cell RNA-sequencing Data
Sam Tracy , Guo-Cheng Yuan , Ruben Dries

STREAM v0.4.1 – Trajectory analysis from Single-cell RNAseq and ATACseq data

STREAM v0.4.1

:: DESCRIPTION

STREAM (Single-cell Trajectories Reconstruction, Exploration And Mapping) is an interactive computational pipeline for reconstructing complex celluar developmental trajectories from sc-qPCR, scRNA-seq or scATAC-seq data

::DEVELOPER

Pinello Lab.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python

:: DOWNLOAD

STREAM

:: MORE INFORMATION

Citation

Nat Commun, 10 (1), 1903 2019 Apr 23
Single-cell Trajectories Reconstruction, Exploration and Mapping of Omics Data With STREAM
Huidong Chen, et al.

Giotto v0.1.4 – Single-cell Spatial Analysis pipeline

Giotto v0.1.4

:: DESCRIPTION

Giotto is a comprehensive pipeline for spatial transcriptomic data analysis and visualization.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R
  • ImageJ library (JAR file)

:: DOWNLOAD

Giotto

:: MORE INFORMATION

Citation

Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data
Ruben Dries, Qian Zhu, Chee-Huat Linus Eng, Arpan Sarkar, Feng Bao, Rani E George, Nico Pierson, Long Cai, Guo-Cheng Yuan
doi: https://doi.org/10.1101/701680

GiniClust3 1.0.1 – Detecting Rare Cell Types from Single-cell Gene Expression data with Gini Index

GiniClust 3 1.0.1

:: DESCRIPTION

GiniClust is a clustering method specifically designed for rare cell type detection. It uses the Gini index to identify genes that are associated with rare cell types without prior knowledge.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python

:: DOWNLOAD

GiniClust

:: MORE INFORMATION

Citation

Rui Dong. Guo-Cheng Yuan.
GiniClust3: a fast and memory-efficient tool for rare cell type identification.

Genome Biol, 17 (1), 144 2016 Jul 1
GiniClust: Detecting Rare Cell Types From Single-Cell Gene Expression Data With Gini Index
Lan Jiang, Huidong Chen, Luca Pinello, Guo-Cheng Yuan

Tsoucas D, Yuan GC.
GiniClust2: a cluster-aware, weighted ensemble clustering method for cell-type detection.
Genome Biology. 2018 May 10;19(1):58.

ECLAIR – Robust Lineage Reconstruction from Single-cell Gene Expression data

ECLAIR

:: DESCRIPTION

ECLAIR (Ensemble Clustering for Lineage Analysis, Inference and Robustness) achieves a higher level of confidence in the estimated lineages through the use of approximation algorithms for consensus clustering and by combining the information from an ensemble of minimum spanning trees so as to come up with an improved, aggregated lineage tree.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python

:: DOWNLOAD

ECLAIR

:: MORE INFORMATION

Citation

Giecold G, Marco E, Trippa L, Yuan GC.
Robust Lineage Reconstruction from High-Dimensional Single-Cell Data.
Nucleic Acids Res. 2016 May 20. pii: gkw452.

SCUBA 1.0 – Single-cell Clustering Using Bifurcation Analysis

SCUBA 1.0

:: DESCRIPTION

SCUBA is a new method for the analysis of single-cell gene expression data. The method is based on a novel combination of dynamic clustering and the mathematical theory of bifurcations.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Matlab

:: DOWNLOAD

 SCUBA

:: MORE INFORMATION

Citation

Marco E, Karp RL, Guo G, Robson P, Hart AH, Trippa L, Yuan GC.
Bifurcation analysis of single-cell gene expression data reveals epigenetic landscape.
Proc Natl Acad Sci U S A. 2014 Dec 30;111(52):E5643-50.

SC1 – A web-based Single Cell RNA-seq Analysis Pipeline

SC1

:: DESCRIPTION

SC1 is a web-based single cell RNA-seq analysis pipeline.

::DEVELOPER

Bioinformatics Lab , Computer Science & Engineering Dept. University of Connecticut

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation:

J Comput Biol. 2019 Aug;26(8):822-835. doi: 10.1089/cmb.2018.0236. Epub 2019 Feb 19.
Locality Sensitive Imputation for Single Cell RNA-Seq Data.
Moussa M, Măndoiu II.