scRNA-tools

A

adobo

adobo is a Python-framework for single cell gene expression data analysis

Publications: 1, Preprints: 0, Total citations: 34

Publications
"alona: a web server for single cell RNA-seq analysis"
DOI: 10.1093/bioinformatics/btaa269, Published: 2020-04-23, Citations: 34

Platform: Python
Code: https://github.com/oscar-franzen/adobo
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License: GPL-3.0
Categories: Cell Cycle, Classification, Clustering, Differential Expression, Dimensionality Reduction, Gene Filtering, Imputation, Normalisation, Quality Control, Visualisation
Added: 2020-05-05, Updated: 2020-05-05

AltAnalyze

AltAnalyze is a multi-functional and easy-to-use software package for automated single-cell and bulk gene and splicing analyses.

Publications: 2, Preprints: 1, Total citations: 516

Publications
"Single-cell analysis of mixed-lineage states leading to a binary cell fate choice"
DOI: 10.1038/nature19348, Published: 2016-08-31, Citations: 459
"cellHarmony: cell-level matching and holistic comparison of single-cell transcriptomes"
DOI: 10.1093/nar/gkz789, Published: 2019-09-16, Citations: 54
Preprints
"cellHarmony: Cell-level matching and holistic comparison of single-cell transcriptomes"
DOI: 10.1101/412080, Citations: 3

Platform: Python
Code: https://github.com/nsalomonis/altanalyze
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License: Apache-2.0
Categories: Alternative Splicing, Cell Cycle, Classification, Clustering, Differential Expression, Dimensionality Reduction, Gene Filtering, Gene Networks, Gene Sets, Interactive, Marker Genes, Normalisation, Quantification, Visualisation
Added: 2017-07-16, Updated: 2018-11-12

ascend

Analysis of Single Cell Expresssion Normalisation and Differential Expression

Publications: 1, Preprints: 1, Total citations: 44

Publications
"ascend: R package for analysis of single-cell RNA-seq data"
DOI: 10.1093/gigascience/giz087, Published: 2019-08-24, Citations: 33
Preprints
"ascend: R package for analysis of single cell RNA-seq data"
DOI: 10.1101/207704, Citations: 11

Platform: R
Code: https://github.com/powellgenomicslab/ascend
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License: GPL-3.0
Categories: Cell Cycle, Clustering, Differential Expression, Dimensionality Reduction, Gene Filtering, Normalisation, Quality Control, Visualisation
Added: 2017-11-20, Updated: 2019-09-23

B

Beyondcell

Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments

Publications: 1, Preprints: 1, Total citations: 49

Publications
"Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq data"
DOI: 10.1186/s13073-021-01001-x, Published: 2021-12, Citations: 49
Preprints
"Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq"
DOI: 10.1101/2021.04.08.438954, Citations: 0

Platform: R
Code: https://gitlab.com/bu_cnio/beyondcell
License: GPL-2.0
Categories: Cell Cycle, Clustering, Dimensionality Reduction, Gene Sets, Perturbations, Visualisation
Added: 2021-04-12, Updated: 2021-12-17

C

CancerInSilico

The CancerInSilico package provides an R interface for running mathematical models of tumor progresson.

Publications: 1, Preprints: 1, Total citations: 3

Publications
"CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer"
DOI: 10.1371/journal.pcbi.1006935, Published: 2019-04-19, Citations: 3
Preprints
"CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer"
DOI: 10.1101/328807, Citations: 0

Platform: R/C++
Code: https://github.com/FertigLab/CancerInSilico
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License: GPL-2.0
Categories: Cell Cycle, Gene Networks, Interactive, Simulation, Visualisation
Added: 2018-06-19, Updated: 2018-06-19

ccAFv2

Single cell RNA-seq cell cycle classifier

Publications: 0, Preprints: 1, Total citations: 0

Preprints
"Breaking out of the cycle: Including quiescence in cell cycle classification"
DOI: 10.1101/2024.04.16.589816, Citations: 0

Platform: R/Python
Code: https://github.com/plaisier-lab/ccafv2
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License: GPL-3.0
Categories: Cell Cycle, Visualisation
Added: 2024-04-26, Updated: 2024-04-26

CCPE

A novel cell cycle pseudotime estimation method to characterize cell cycle timing and determine cell cycle phases from single-cell RNA-seq data

Publications: 1, Preprints: 1, Total citations: 15

Publications
"CCPE: cell cycle pseudotime estimation for single cell RNA-seq data"
DOI: 10.1093/nar/gkab1236, Published: 2021-12-21, Citations: 14
Preprints
"CCPE: Cell Cycle Pseudotime Estimation for Single Cell RNA-seq Data"
DOI: 10.1101/2021.06.13.448263, Citations: 1

Platform: MATLAB
Code: https://github.com/LiuJJ0327/CCPE
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Categories: Cell Cycle
Added: 2021-06-18, Updated: 2022-01-06

ccRemover

Implements a method for identifying and removing the cell-cycle effect from scRNA-Seq data.

Publications: 1, Preprints: 1, Total citations: 98

Publications
"Identifying and removing the cell-cycle effect from single-cell RNA-Sequencing data"
DOI: 10.1038/srep33892, Published: 2016-09-27, Citations: 98
Preprints
"Identifying and removing the cell-cycle effect from single-cell RNA-Sequencing data"
arXiv: 1605.04492, Citations: 0

Platform: R
Code: https://github.com/cran/ccRemover
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License: GPL-3.0
Categories: Cell Cycle
Added: 2018-04-23, Updated: 2018-04-23

cellmarkeraccordion

R package for automatically annotating and interpreting single-cell populations

Publications: 0, Preprints: 1, Total citations: 2

Preprints
"Interpreting single-cell messages in normal and aberrant hematopoiesis with the Cell Marker Accordion"
DOI: 10.1101/2024.03.08.584053, Citations: 2

Platform: R
Code: https://github.com/TebaldiLab/cellmarkeraccordion
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License: MIT
Categories: Cell Cycle, Classification, Visualisation
Added: 2024-03-15, Updated: 2024-03-15

CoSpar

Dynamic inference by integrating state and lineage information

Publications: 1, Preprints: 1, Total citations: 65

Publications
"CoSpar identifies early cell fate biases from single-cell transcriptomic and lineage information"
DOI: 10.1038/s41587-022-01209-1, Published: 2022-02-21, Citations: 63
Preprints
"Learning dynamics by computational integration of single cell genomic and lineage information"
DOI: 10.1101/2021.05.06.443026, Citations: 2

Platform: Python
Code: https://github.com/AllonKleinLab/cospar
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License: MIT
Categories: Cell Cycle, Ordering, Variable Genes, Visualisation
Added: 2021-05-14, Updated: 2022-03-04

Cyclum

Cyclum is a package to recover cell cycle information and remove cell cycle factors from scRNA-seq data

Publications: 1, Preprints: 1, Total citations: 31

Publications
"Latent periodic process inference from single-cell RNA-seq data"
DOI: 10.1038/s41467-020-15295-9, Published: 2020-03-18, Citations: 31
Preprints
"Latent periodic process inference from single-cell RNA-seq data"
DOI: 10.1101/625566, Citations: 0

Platform: Python
Code: https://github.com/KChen-lab/cyclum
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License: MIT
Categories: Cell Cycle, Dimensionality Reduction
Added: 2019-05-07, Updated: 2021-06-28

D

DeepCycle

Cell cycle analysis with RNA velocity and deep-learning

Publications: 1, Preprints: 1, Total citations: 50

Publications
"Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning"
DOI: 10.1038/s41467-022-30545-8, Published: 2022-05-23, Citations: 50
Preprints
"Cell cycle gene regulation dynamics revealed by RNA velocity and deep-learning"
DOI: 10.1101/2021.03.17.435887, Citations: 0

Platform: Python
Code: https://github.com/andreariba/DeepCycle
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License: GPL-3.0
Categories: Cell Cycle, Dimensionality Reduction, Ordering
Added: 2021-03-26, Updated: 2022-06-17

DoubletDecon

A cell-state aware tool for removing doublets from single-cell RNA-seq data.

Publications: 2, Preprints: 2, Total citations: 176

Publications
"DoubletDecon: Deconvoluting Doublets from Single-Cell RNA-Sequencing Data"
DOI: 10.1016/j.celrep.2019.09.082, Published: 2019-11, Citations: 155
"Protocol for Identification and Removal of Doublets with DoubletDecon"
DOI: 10.1016/j.xpro.2020.100085, Published: 2020-09, Citations: 6
Preprints
"Identification and Removal of Doublets with DoubletDecon"
DOI: 10.1101/2020.04.23.058156, Citations: 0
"DoubletDecon: Cell-State Aware Removal of Single-Cell RNA-Seq Doublets"
DOI: 10.1101/364810, Citations: 15

Platform: R
Code: https://github.com/EDePasquale/DoubletDecon
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License: MIT
Categories: Cell Cycle, Quality Control
Added: 2018-07-28, Updated: 2020-08-20

F

fusca

Framework for Unified Single-Cell Analysis (FUSCA) is a software package for single-cell data analysis developed in R

Publications: 1, Preprints: 0, Total citations: 19

Publications
"CellComm infers cellular crosstalk that drives haematopoietic stem and progenitor cell development"
DOI: 10.1038/s41556-022-00884-1, Published: 2022-04-12, Citations: 19

Platform: R/Java
Code: https://github.com/edroaldo/fusca
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License: MIT
Categories: Cell Cycle, Clustering, Dimensionality Reduction, Gene Networks, Gene Sets, Marker Genes, Normalisation, Ordering, Variable Genes, Visualisation
Added: 2022-05-03, Updated: 2022-05-03

I

IBRAP

IBRAP is an R-based package that has integrated many scRNA-seq analytical methods into a single pipeline

Publications: 1, Preprints: 1, Total citations: 5

Publications
"IBRAP: integrated benchmarking single-cell RNA-sequencing analytical pipeline"
DOI: 10.1093/bib/bbad061, Published: 2023-02-27, Citations: 5
Preprints
"IBRAP: Integrated Benchmarking Single-cell RNA-sequencing Analytical Pipeline"
DOI: 10.1101/2022.09.26.509481, Citations: 0

Platform: R
Code: https://github.com/connorhknight/IBRAP
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License: GPL-3.0
Categories: Cell Cycle, Classification, Clustering, Differential Expression, Gene Sets, Integration, Normalisation, Ordering, Quality Control, Variable Genes, Visualisation
Added: 2023-05-05, Updated: 2023-05-05

ICARUS

Welcome to ICARUS (Interactive single Cell RNA-seq Analysis with R shiny Using Seurat)

Publications: 2, Preprints: 1, Total citations: 36

Publications
"ICARUS, an interactive web server for single cell RNA-seq analysis"
DOI: 10.1093/nar/gkac322, Published: 2022-05-10, Citations: 31
"Delineation of complex gene expression patterns in single cell RNA-seq data with ICARUS v2.0"
DOI: 10.1093/nargab/lqad032, Published: 2022-06-01, Citations: 4
Preprints
"Delineation of complex gene expression patterns in single cell RNA-seq data with ICARUS v2.0"
DOI: 10.1101/2023.01.23.525100, Citations: 1

Platform: R
Code: https://github.com/Enjewl/ICARUS
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License: MIT
Categories: Cell Cycle, Classification, Differential Expression, Dimensionality Reduction, Gene Networks, Gene Sets, Imputation, Interactive, Marker Genes, Quality Control, Variants, Visualisation
Added: 2023-01-27, Updated: 2023-05-12

iCellR

iCellR is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq and CITE-seq)

Publications: 0, Preprints: 2, Total citations: 10

Preprints
"iCellR: Combined Coverage Correction and Principal Component Alignment for Batch Alignment in Single-Cell Sequencing Analysis"
DOI: 10.1101/2020.03.31.019109, Citations: 8
"Graph Drawing-based Dimensionality Reduction to Identify Hidden Communities in Single-Cell Sequencing Spatial Representation"
DOI: 10.1101/2020.05.05.078550, Citations: 2

Platform: R
Code: https://github.com/rezakj/iCellR
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License: GPL-2.0
Categories: Cell Cycle, Clustering, Differential Expression, Dimensionality Reduction, Imputation, Integration, Marker Genes, Normalisation, Quality Control, Visualisation
Added: 2020-04-13, Updated: 2020-05-08

O

OscoNet

Method to infer sinusoidal oscillations in single cell data

Publications: 1, Preprints: 1, Total citations: 3

Publications
"OscoNet: inferring oscillatory gene networks"
DOI: 10.1186/s12859-020-03561-y, Published: 2020-08-25, Citations: 3
Preprints
"OscoNet: Inferring oscillatory gene networks"
DOI: 10.1101/600049, Citations: 0

Platform: Python/R
Code: https://github.com/alexisboukouvalas/OscoNet
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License: MIT
Categories: Cell Cycle, Expression Patterns, Ordering
Added: 2020-09-10, Updated: 2020-09-10

Oscope

Oscope: a statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq experiments.

Publications: 1, Preprints: 0, Total citations: 166

Publications
"Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments"
DOI: 10.1038/nmeth.3549, Published: 2015-08-24, Citations: 166

Platform: R
License: Artistic-2.0
Categories: Cell Cycle
Added: 2016-09-09, Updated: 2018-03-15

P

peco

peco is an R package for predicting cell cycle progression in a continnum using scRNA-seq data.

Publications: 1, Preprints: 1, Total citations: 75

Publications
"Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis"
DOI: 10.1101/gr.247759.118, Published: 2020-04-20, Citations: 72
Preprints
"Characterizing and inferring quantitative cell cycle phase in single-cell RNA-seq data analysis"
DOI: 10.1101/526848, Citations: 3

Platform: R
Code: https://github.com/jhsiao999/peco
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License: GPL-3.0
Categories: Cell Cycle
Added: 2019-02-11, Updated: 2021-06-28

Pre-Phaser

Cell-Cycle Phase Detector for scRNA-seq

Publications: 1, Preprints: 0, Total citations: 0

Publications
"Pre-Phaser"
DOI: 10.1145/3307339.3342174, Published: 2019-09-04, Citations: 0

Platform: Python/C++
Code: https://github.com/ayurovsky/Pre-Phaser
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Categories: Cell Cycle
Added: 2019-09-17, Updated: 2019-09-17

R

rCASC

rCASC, Cluster Analysis of Single Cells

Publications: 2, Preprints: 2, Total citations: 63

Publications
"Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining"
DOI: 10.1038/s41540-020-00162-6, Published: 2021-01-05, Citations: 34
"rCASC: reproducible classification analysis of single-cell sequencing data"
DOI: 10.1093/gigascience/giz105, Published: 2019-09-08, Citations: 28
Preprints
"Sparsely-Connected Autoencoder (SCA) for single cell RNAseq data mining"
DOI: 10.1101/2020.05.26.117705, Citations: 0
"rCASC: reproducible Classification Analysis of Single Cell sequencing data"
DOI: 10.1101/430967, Citations: 1

Platform: R/Docker
Code: https://github.com/kendomaniac/rCASC
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License: GPL-3.0
Categories: Alignment, Cell Cycle, Clustering, Dimensionality Reduction, Gene Filtering, Marker Genes, Normalisation, Quality Control, Quantification, UMIs, Visualisation
Added: 2018-11-14, Updated: 2020-06-05

reCAT

reCAT is a modelling framework for unsynchronized single-cell transcriptome data that can reconstruct a high-resolution cell cycle time-series.

Publications: 1, Preprints: 0, Total citations: 125

Publications
"Reconstructing cell cycle pseudo time-series via single-cell transcriptome data"
DOI: 10.1038/s41467-017-00039-z, Published: 2017-06-19, Citations: 125

Platform: R
Code: https://github.com/tinglab/reCAT
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Categories: Cell Cycle, Clustering, Ordering, Visualisation
Added: 2017-07-16, Updated: 2017-07-16

Revelio

The Revelio package is designed to extract cell cycle information from scRNA-seq experiments of cycling cells

Publications: 1, Preprints: 0, Total citations: 55

Publications
"The transcriptome dynamics of single cells during the cell cycle"
DOI: 10.15252/msb.20209946, Published: 2020-11, Citations: 55

Platform: R
Code: https://github.com/danielschw188/Revelio
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Categories: Cell Cycle, Ordering, Visualisation
Added: 2021-06-25, Updated: 2021-06-25

S

SCALA

A web application for multimodal analysis of single cell next generation sequencing data

Publications: 1, Preprints: 1, Total citations: 3

Publications
"SCALA: A complete solution for multimodal analysis of single-cell Next Generation Sequencing data"
DOI: 10.1016/j.csbj.2023.10.032, Published: 2023, Citations: 2
Preprints
"SCALA: A web application for multimodal analysis of single cell next generation sequencing data"
DOI: 10.1101/2022.11.24.517826, Citations: 1

Platform: R/JavaScript
Code: https://github.com/PavlopoulosLab/SCALA
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License: GPL-3.0
Categories: Cell Cycle, Classification, Clustering, Differential Expression, Dimensionality Reduction, Expression Patterns, Gene Filtering, Gene Networks, Integration, Interactive, Marker Genes, Normalisation, Ordering, Quality Control, Variable Genes, Visualisation
Added: 2023-11-17, Updated: 2023-11-17

scarf

Scarf is a Python package to performs memory efficient analysis of single-cell genomics data

Publications: 1, Preprints: 1, Total citations: 22

Publications
"Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data"
DOI: 10.1038/s41467-022-32097-3, Published: 2022-08-08, Citations: 21
Preprints
"Scarf: A toolkit for memory efficient analysis of large-scale single-cell genomics data"
DOI: 10.1101/2021.05.02.441899, Citations: 1

Platform: Python
Code: https://github.com/parashardhapola/scarf
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License: BSD-3-Clause
Categories: Cell Cycle, Clustering, Differential Expression, Dimensionality Reduction, Gene Filtering, Imputation, Marker Genes, Normalisation, Ordering, Quality Control, Variable Genes, Visualisation
Added: 2021-05-07, Updated: 2022-08-26

scCancer

The scCancer package focuses on processing and analyzing droplet-based scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features.

Publications: 1, Preprints: 1, Total citations: 54

Publications
"scCancer: a package for automated processing of single-cell RNA-seq data in cancer"
DOI: 10.1093/bib/bbaa127, Published: 2020-07-06, Citations: 51
Preprints
"scCancer: a package for automated processing of single cell RNA-seq data in cancer"
DOI: 10.1101/800490, Citations: 3

Platform: R
Code: https://github.com/wguo-research/scCancer
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License: GPL-3.0
Categories: Cell Cycle, Classification, Clustering, Differential Expression, Gene Networks, Quality Control, Stem Cells
Added: 2019-10-30, Updated: 2019-10-30

scCancer2

An updated our R toolkit, scCancer, based on massive single-cell transcriptome and spatial transcriptome data

Publications: 1, Preprints: 1, Total citations: 1

Publications
"scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution"
DOI: 10.1093/bioinformatics/btae028, Published: 2024-01-18, Citations: 1
Preprints
"scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution"
DOI: 10.1101/2023.08.22.554137, Citations: 0

Platform: R
Code: https://github.com/czythu/scCancer
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License: MIT
Categories: Cell Cycle, Clustering, Gene Networks, Integration, Stem Cells, Visualisation
Added: 2023-08-24, Updated: 2024-05-06

scdrake

{scdrake} is a scalable and reproducible pipeline for secondary analysis of droplet-based single-cell RNA-seq data

Publications: 1, Preprints: 0, Total citations: 3

Publications
"Scdrake: a reproducible and scalable pipeline for scRNA-seq data analysis"
DOI: 10.1093/bioadv/vbad089, Published: 2023-07-06, Citations: 3

Platform: R
Code: https://github.com/bioinfocz/scdrake
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License: MIT
Categories: Cell Cycle, Classification, Clustering, Dimensionality Reduction, Integration, Marker Genes, Normalisation, Quality Control, Variable Genes, Visualisation
Added: 2023-07-14, Updated: 2023-07-14

scLVM

scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation. scLVM was primarily designed to account for cell-cycle induced variations in single-cell RNA-seq data where cell cycle is the primary soure of variability.

Publications: 1, Preprints: 0, Total citations: 1061

Publications
"Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells"
DOI: 10.1038/nbt.3102, Published: 2015-01-19, Citations: 1061

Platform: R/Python
Code: https://github.com/PMBio/scLVM
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License: Apache-2.0
Categories: Cell Cycle, Normalisation, Variable Genes, Visualisation
Added: 2016-09-08, Updated: 2016-12-08

scran

This package implements a variety of low-level analyses of single-cell RNA-seq data. Methods are provided for normalization of cell-specific biases, pool-based norms to estimate size factors, assignment of cell cycle phase, and detection of highly variable and significantly correlated genes.

Publications: 2, Preprints: 1, Total citations: 2823

Publications
"Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors"
DOI: 10.1038/nbt.4091, Published: 2018-04-02, Citations: 1877
"Pooling across cells to normalize single-cell RNA sequencing data with many zero counts"
DOI: 10.1186/s13059-016-0947-7, Published: 2016-04-27, Citations: 928
Preprints
"Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours"
DOI: 10.1101/165118, Citations: 18

Platform: R
Code: https://github.com/MarioniLab/scran
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License: GPL-3.0
Categories: Cell Cycle, Integration, Interactive, Normalisation, Variable Genes, Visualisation
Added: 2016-09-08, Updated: 2018-04-02

SCRAT

Single Cell R Analysis Toolkit
Platform: R
Code: http://www.treutleinlab.org/scrat-single-cell-r-analysis-toolkit/
License: GPL-2.0-or-later
Categories: Cell Cycle, Clustering, Dimensionality Reduction, Gene Networks, Normalisation, Ordering, Quality Control, Visualisation
Added: 2018-06-19, Updated: 2018-06-19

signifinder

signifinder is an R package that collects and implements 46 expression-based signatures from cancer literature

Publications: 0, Preprints: 1, Total citations: 1

Preprints
"signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data"
DOI: 10.1101/2023.03.07.530940, Citations: 1

Platform: R
Code: https://github.com/CaluraLab/signifinder
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License: AGPL-3.0
Categories: Cell Cycle, Gene Sets, Immune, Visualisation
Added: 2023-03-17, Updated: 2023-03-17

SingCellaR

An integrative analysis tool for analysing single-cell RNA sequencing data

Publications: 1, Preprints: 0, Total citations: 8

Publications
"Processing single-cell RNA-seq datasets using SingCellaR"
DOI: 10.1016/j.xpro.2022.101266, Published: 2022-06, Citations: 8

Platform: R/C++
Code: https://github.com/supatt-lab/SingCellaR
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License: GPL-3.0
Categories: Cell Cycle, Clustering, Differential Expression, Dimensionality Reduction, Gene Filtering, Gene Sets, Integration, Marker Genes, Quality Control, Visualisation
Added: 2022-04-08, Updated: 2022-04-08

T

tauFisher

Circadian time prediction from genomic data

Publications: 0, Preprints: 1, Total citations: 2

Preprints
"tauFisher accurately predicts circadian time from a single sample of bulk and single-cell transcriptomic data"
DOI: 10.1101/2023.04.04.535473, Citations: 2

Platform: R
Code: https://github.com/micnngo/tauFisher
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License: GPL-3.0
Categories: Cell Cycle
Added: 2023-05-05, Updated: 2023-05-05

Tempo

A Bayesian Algorithm for Circadian Phase Inference in Single-Cell RNA-Sequencing Data

Publications: 1, Preprints: 1, Total citations: 13

Publications
"Tempo: an unsupervised Bayesian algorithm for circadian phase inference in single-cell transcriptomics"
DOI: 10.1038/s41467-022-34185-w, Published: 2022-11-02, Citations: 13
Preprints
"Tempo: an unsupervised Bayesian algorithm for circadian phase inference in single-cell transcriptomics"
DOI: 10.1101/2022.03.15.484454, Citations: 0

Platform: Python
Code: https://github.com/bauerbach95/tempo
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License: MIT
Categories: Cell Cycle
Added: 2022-03-25, Updated: 2023-01-04

tricycle

Transferable Representation and Inference of cell cycle

Publications: 1, Preprints: 1, Total citations: 62

Publications
"Universal prediction of cell-cycle position using transfer learning"
DOI: 10.1186/s13059-021-02581-y, Published: 2022-01-31, Citations: 57
Preprints
"Universal prediction of cell cycle position using transfer learning"
DOI: 10.1101/2021.04.06.438463, Citations: 5

Platform: R
Code: https://github.com/hansenlab/tricycle
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License: GPL-3.0
Categories: Cell Cycle, Dimensionality Reduction, Visualisation
Added: 2021-04-12, Updated: 2022-03-04

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VeloCycle

Manifold-constrained variational inference for RNA velocity of the cell cycle

Publications: 0, Preprints: 1, Total citations: 6

Preprints
"Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations"
DOI: 10.1101/2024.01.18.576093, Citations: 6

Platform: Python
Code: https://github.com/lamanno-epfl/velocycle
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License: CC-BY-NC-ND-4.0
Categories: Cell Cycle, Gene Filtering, Normalisation, Ordering, Visualisation
Added: 2024-02-02, Updated: 2024-02-02

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