Methods packages listed below are tools for performing analyses involving computational biology approaches for analyzing single-cell data. Method software is pre-installed in container images. Registry methods can be called programmatically for easy integration into portals. These methods provide domain-specific ways to analyze biological data produced by Human Cell Atlas.
These solutions are built by third parties, and fostered by the HCA DCP.
Are you developing a package that can consume HCA data? Please submit it for inclusion in the registry.
Brian J. Haas, Christophe H. Georgescu, Maxwell P. Brown, Timothy L. Tickle, Livnat Jerby, Matan Hofree, Itay Tirosh, Aviv Regev
InferCNV is used to explore tumor single cell RNA-Seq data to identify evidence for large-scale chromosomal copy number variations.
David van Dijk, Kevin Moon, Scott Gigante, Daniel Dager, Guy Wolf, Smita Krishnaswamy
Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising and imputation of single cells applied to single-cell RNA sequencing data
Kevin Moon, David van Dijk, Scott Gigante, Smita Krishnaswamy
PHATE is a tool for visualizing high dimensional single-cell data with natural progressions or trajectories.
Martin Hemberg (SC3), Gene Expression Team (sc3-scripts)
SC3 is an unsupervised clustering method for scRNA-seq data.
Kelly Street, Davide Risso, Diya Das, Sandrine Dudoit, Koen Van den Berge, and Robrecht Cannoodt
Slingshot provides functions for inferring continuous, branching lineage structures in low-dimensional data.
Huidong Chen, Luca Pinello
STREAM is an interactive computational pipeline for reconstructing complex cellular developmental trajectories from sc-qPCR, scRNA-seq or scATAC-seq data.