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A

B

C

  • CellPhoneDB is a publicly available repository of curated receptors, ligands and interactions.

    • Publications
    • "Single-cell reconstruction of the early maternal–fetal interface in humans"
      DOI: 10.1038/s41586-018-0698-6, Published: 2018-11-14, Citations: 1669
    • "CellPhoneDB: inferring cell–cell communication from combined expression of multi-subunit ligand–receptor complexes"
      DOI: 10.1038/s41596-020-0292-x, Published: 2020-02-26, Citations: 2234
    • Preprints
    • "Reconstructing the human first trimester fetal–maternal interface using single cell transcriptomics"
      DOI: 10.1101/429589, Citations: 5
    • "CellPhoneDB v2.0: Inferring cell-cell communication from combined expression of multi-subunit receptor-ligand complexes"
      DOI: 10.1101/680926, Citations: 54
    • "CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data"
      arXiv: 2311.04567, Citations: 0
  • Platform: Python
  • Code: https://github.com/Teichlab/cellphonedb
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  • License: MIT
  • Categories: Gene Networks, Visualisation
  • Added: 2018-11-16, Updated: 2023-11-17

  • Clustergrammer2 is an interactive WebGL heatmap Jupyter widget that is built to help researchers interactively explore single cell data (e.g. scRNA-seq). Clustergrammer2 enables unbiased hierarchical clustering, integration of prior knowledge categories, and the generation of novel signatures.
  • Platform: Python
  • Code: https://github.com/ismms-himc/clustergrammer2
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  • License: MIT
  • Categories: Classification, Clustering, Gene Sets, Interactive, Visualisation
  • Added: 2019-11-06, Updated: 2021-06-28

  • ctgGEM is an R package that combines a variety of visualization packages for single cell RNA tree hierarchies
  • Platform: R
  • Code: https://github.com/bicbioeng/ctgGEM
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  • License: GPL-2.0-or-later
  • Categories: Visualisation
  • Added: 2020-04-29, Updated: 2020-04-29

D

  • DENDRO, stands for Dna based EvolutioNary tree preDiction by scRna-seq technOlogy, is an R package, which takes scRNA-seq data for a tumor (or related somatic tissues) and accurately reconstructs its phylogeny, assigning each single cell from the single cell RNA sequencing (scRNA-seq) data to a subclone.

    • Publications
    • "DENDRO: genetic heterogeneity profiling and subclone detection by single-cell RNA sequencing"
      DOI: 10.1186/s13059-019-1922-x, Published: 2020-01-14, Citations: 43
    • Preprints
    • "Genetic Heterogeneity Profiling by Single Cell RNA Sequencing"
      DOI: 10.1101/457622, Citations: 1
  • Platform: R
  • Code: https://github.com/zhouzilu/DENDRO
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  • License: GPL-3.0
  • Categories: Clustering, Simulation, Variants, Visualisation
  • Added: 2018-11-14, Updated: 2020-01-22

E

  • EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific omics measurements from single-cell sequencing

    • Publications
    • "EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing"
      DOI: 10.1371/journal.pgen.1010251, Published: 2022-06-16, Citations: 12
    • Preprints
    • "EPIC: inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing"
      DOI: 10.1101/2021.06.09.447805, Citations: 2
  • Platform: R
  • Code: https://github.com/rujinwang/EPIC
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  • License: GPL-2.0
  • Categories: Variants, Visualisation
  • Added: 2021-06-25, Updated: 2022-06-17

F

G

  • Useful functions to visualize single cell and spatial data.
  • Platform: R/C++
  • Code: https://github.com/YuLab-SMU/ggsc
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  • License: Artistic-2.0
  • Categories: Visualisation
  • Added: 2023-11-03, Updated: 2023-11-03

H

I

  • With this package .fsa intensity files or files with sequencing lengths representing the CDR3 region of T-cell receptors can be loaded, visualized and scored for quantification of the immune repertoire.
  • Platform: R
  • Code: https://github.com/martijn-cordes/ImSpectR
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  • License: MIT
  • Categories: Quantification, Visualisation
  • Added: 2019-11-08, Updated: 2019-11-08

  • Iscandar (Interactive Single Cell Data Analysis Report) is a set of python scripts and html/javascript files used to create interactive report for single cell rna-seq analysis.
  • Platform: Python
  • Code: https://github.com/jarny/iscandar
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  • License: MIT
  • Categories: Interactive, Visualisation
  • Added: 2017-11-20, Updated: 2017-11-20

J

K

L

M

  • MarkovHC as a novel single-cell omics data analysis tool, can facilitate the stratification of cells, identification of cell population hierarchical structures, and characterization of cellular trajectories and critical points

    • Publications
    • "MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data with transition pathway and critical point detection"
      DOI: 10.1093/nar/gkab1132, Published: 2021-12-01, Citations: 9
    • Preprints
    • "MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data"
      DOI: 10.1101/2020.11.04.368043, Citations: 1
  • Platform: R
  • Code: https://github.com/ZhenyiWangTHU/MarkovHC
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  • License: GPL-3.0
  • Categories: Clustering, Visualisation
  • Added: 2021-12-10, Updated: 2021-12-10

  • MIRA (Probabilistic Multimodal Models for Integrated Regulatory Analysis) is a comprehensive methodology that systematically contrasts single cell transcription and accessibility to infer the regulatory circuitry driving cells along developmental trajectories

    • Publications
    • "Multi-batch single-cell comparative atlas construction by deep learning disentanglement"
      DOI: 10.1038/s41467-023-39494-2, Published: 2023-07-12, Citations: 6
    • "MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells"
      DOI: 10.1038/s41592-022-01595-z, Published: 2022-09-06, Citations: 47
    • Preprints
    • "MIRA: Joint regulatory modeling of multimodal expression and chromatin accessibility in single cells"
      DOI: 10.1101/2021.12.06.471401, Citations: 0
  • Platform: Python
  • Code: https://github.com/cistrome/MIRA
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  • Categories: Integration, Ordering, Visualisation
  • Added: 2021-12-10, Updated: 2023-07-21

N

O

P

  • The term creode was coined by C.H. Waddington, combining the Greek words for “necessary” and “path” to describe the cell state transitional trajectories that define cell fate specification. Our algorithm aims to identify consensus routes from relatively noisy single-cell data and thus we named this algorithm p- (putative) Creode.

    • Publications
    • "Unsupervised Trajectory Analysis of Single-Cell RNA-Seq and Imaging Data Reveals Alternative Tuft Cell Origins in the Gut"
      DOI: 10.1016/j.cels.2017.10.012, Published: 2018-01, Citations: 172
  • Platform: Python
  • Code: https://github.com/KenLauLab/pCreode
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  • License: GPL-2.0
  • Categories: Dimensionality Reduction, Ordering, Visualisation
  • Added: 2017-12-07, Updated: 2021-06-28

  • R package providing functions for fitting, analyzing and visualizing single-cell RNASeq data which has been quantified by counting UMIs while accounting for different sequencing depths/detection rates between cells.
  • Platform: R
  • Code: https://github.com/tallulandrews/PoissonUMIs
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  • License: GPL-2.0
  • Categories: UMIs, Visualisation
  • Added: 2016-10-10, Updated: 2017-09-25

R

S

  • scCustomize is a collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R
  • Platform: R
  • Code: https://github.com/samuel-marsh/scCustomize
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  • License: GPL-3.0
  • Categories: Visualisation
  • Added: 2021-11-20, Updated: 2023-01-04

  • scDesign3 is an all-in-one single-cell data simulation tool by using reference datasets with different cell states(cell types, trajectories or and spatial coordinates), different modalities(gene expression, chromatin accessibility, protein abundance, methylation,etc), and complex experimental designs

    • Publications
    • "scDesign3 generates realistic in silico data for multimodal single-cell and spatial omics"
      DOI: 10.1038/s41587-023-01772-1, Published: 2023-05-11, Citations: 54
    • Preprints
    • "A unified framework of realistic in silico data generation and statistical model inference for single-cell and spatial omics"
      DOI: 10.1101/2022.09.20.508796, Citations: 4
  • Platform: R
  • Code: https://github.com/SONGDONGYUAN1994/scDesign3
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  • License: MIT
  • Categories: Simulation, Visualisation
  • Added: 2022-12-16, Updated: 2023-10-27

  • Single cell Higher Order Testing (scHOT) is an R package that facilitates testing changes in higher order structure of gene expression along either a developmental trajectory or across space
  • Platform: R
  • Code: https://github.com/shazanfar/scHOT
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  • License: GPL-3.0
  • Categories: Expression Patterns, Visualisation
  • Added: 2020-04-29, Updated: 2020-04-29

  • 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
    • "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

  • SCPA is a method for pathway analysis in single cell RNA-seq data. It’s a novel approach to pathway analysis that defines pathway activity as a change in multivariate distribution of a given pathway across conditions, rather than enrichment or over representation of genes.

    • Publications
    • "Systematic single-cell pathway analysis to characterize early T cell activation"
      DOI: 10.1016/j.celrep.2022.111697, Published: 2022-11, Citations: 50
    • Preprints
    • "Systematic Single Cell Pathway Analysis (SCPA) reveals novel pathways engaged during early T cell activation"
      DOI: 10.1101/2022.02.07.478807, Citations: 0
  • Platform: R
  • Code: https://github.com/jackbibby1/SCPA
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  • License: GPL-3.0
  • Categories: Gene Sets, Visualisation
  • Added: 2022-02-11, Updated: 2023-01-04

  • The goal of scRAS is to measure the cell state deviation (CSD) and cell anomalousness score (CAS) which are indicators of whether one individual cell is remote from the average expression states and whether a cell is locally anomalous, respectively
  • Platform: R
  • Code: https://github.com/AristoQian/scRAS
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  • License: MIT
  • Categories: Rare Cells, Visualisation
  • Added: 2022-12-09, Updated: 2022-12-09

  • This package provides methods to interactively explore and visualize datasets with hierarchies. eg. single cells datasets with hierarchy over cells at different resolutions
  • Platform: R
  • Code: https://github.com/HCBravoLab/scTreeViz
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  • License: Artistic-2.0
  • Categories: Interactive, Visualisation
  • Added: 2021-10-29, Updated: 2021-10-29

  • Existing computational approaches for the assessment of cell-state hierarchies from single-cell data might be formalized under a general workflow composed of i) a metric to assess cell-to-cell similarities (combined or not with a dimensionality reduction step), and ii) a graph-building algorithm (optionally making use of a cells-clustering step). Sincell R package implements a methodological toolbox allowing flexible workflows under such framework.

    • Publications
    • "Sincell: an R/Bioconductor package for statistical assessment of cell-state hierarchies from single-cell RNA-seq: Fig. 1."
      DOI: 10.1093/bioinformatics/btv368, Published: 2015-06-22, Citations: 51
    • Preprints
    • "Sincell: Bioconductor package for the statistical assessment of cell-state hierarchies from single-cell RNA-seq data"
      DOI: 10.1101/014472, Citations: 3
  • Platform: R
  • License: GPL-2.0-or-later
  • Categories: Clustering, Dimensionality Reduction, Ordering, Visualisation
  • Added: 2016-09-08, Updated: 2018-03-15

T

  • TreeCorTreat is an open source R package that uses a tree-based correlation screen to analyze and visualize the association between phenotype and transcriptomic features and cell types at multiple cell type resolution levels

    • Preprints
    • "Tree-based Correlation Screen and Visualization for Exploring Phenotype-Cell Type Association in Multiple Sample Single-Cell RNA-Sequencing Experiments"
      DOI: 10.1101/2021.10.27.466024, Citations: 1
  • Platform: R
  • Code: https://github.com/byzhang23/TreeCorTreat
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  • License: GPL-3.0
  • Categories: Visualisation
  • Added: 2021-11-05, Updated: 2021-11-12

U

V

  • This package provides functions for handling and analyzing immune receptor repertoire data, such as produced by the CellRanger V(D)J pipeline
  • Platform: R
  • Code: https://github.com/kstreet13/VDJdive
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  • License: Artistic-2.0
  • Categories: Immune, Integration, Visualisation
  • Added: 2022-11-04, Updated: 2022-11-04

W

  • Waddington-OT uses time-course data to infer how the probability distribution of cells in gene-expression space evolves over time, by using the mathematical approach of Optimal Transport (OT).

    • Publications
    • "Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming"
      DOI: 10.1016/j.cell.2019.01.006, Published: 2019-02, Citations: 500
    • Preprints
    • "Reconstruction of developmental landscapes by optimal-transport analysis of single-cell gene expression sheds light on cellular reprogramming"
      DOI: 10.1101/191056, Citations: 33
  • Platform: Python/Java
  • Code: https://github.com/broadinstitute/wot
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  • License: BSD-3-Clause
  • Categories: Ordering, Visualisation
  • Added: 2019-02-11, Updated: 2019-02-11

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