Tag: Single Cell

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.

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

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.

VirtualCytometry – Webserver for the Study of Immune Cell Differentiation using single-cell RNA sequencing data

VirtualCytometry

:: DESCRIPTION

VirtualCytometry is a webserver that provides computational platform for the study of immune cell differentiation using scRNA-seq data by enabling identification and validation of genes involved in immune cell differentiations via ‘Discovery Module’ and ‘Hypothesis Test Module’ respectively.

::DEVELOPER

Network Biomedicine Laboratory at Yonsei University, Korea

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2019 Aug 2. pii: btz610. doi: 10.1093/bioinformatics/btz610.
VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data.
Kim K, Yang S, Ha SJ, Lee I.

QSpec 1.0 / QSpec-Simu 1.0 – A Raman Spectrum Acquisition and Analysis System for Single-Cell

QSpec 1.0 / QSpec-Simu 1.0

:: DESCRIPTION

QSpec is an open-source framework of microorganism single-cell experimental platform that could support the full cycle of single-cell phenotyping: instrument control (including RACS platform control and microfluidic device control), single-cell image analysis, single-cell Raman profiling, single-cell profile comparison, etc.

QSpec-Simu is an open-source framework of virtual microorganism single-cell experimental platform

::DEVELOPER

Bioinformatics Group , Single-cell Reseearch Center of Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences (QIBEBT-CAS).

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

QSpec / QSpec-Simu

:: MORE INFORMATION

Citation

Lihui R.; Xiaoquan S.; Yun W.; Jian X.; Kang N.,
QSpec: online control and data analysis system for single-cell Raman spectroscopy.
PeerJ. 2014 Jun 26;2:e436. doi: 10.7717/peerj.436. eCollection 2014.

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

TLM-Tracker – Single Cell analyses in Live-cell Imaging experiments

TLM-Tracker

:: DESCRIPTION

TLM-Tracker (Time-Lapse-Movie-Tracker) is a free platform independent tool for single cell analyses in live-cell imaging experiments like time lapse microscopy. It allows for the flexible and user friendly segmentation, tracking and lineage analysis of microbial cells in time-lapse movies.

::DEVELOPER

TLM-Tracker Team

:: SCREENSHOTS

TLM-Tracker

:: REQUIREMENTS

:: DOWNLOAD

 TLM-Tracker

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Sep 1;28(17):2276-7. doi: 10.1093/bioinformatics/bts424. Epub 2012 Jul 5.
TLM-Tracker: software for cell segmentation, tracking and lineage analysis in time-lapse microscopy movies.
Klein J, Leupold S, Biegler I, Biedendieck R, Münch R, Jahn D.