splikit - Analysing RNA Splicing in Single-Cell RNA Sequencing Data
Provides analysis of high-dimensional single-cell splicing data. Offers a framework to extract and work with ratio-based data structures derived from single-cell RNA sequencing experiments. Provides both a modern 'R6' object-oriented interface and direct matrix manipulation functions. Core functionalities are implemented in 'C++' via 'Rcpp' to ensure high performance and scalability on large datasets.
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rna-splicingsingle-cell-geopenblascppopenmp
5.29 score 1 stars 6 scripts 545 downloadsgedi2 - Gene Expression Decomposition and Integration
A memory-efficient implementation for integrating gene expression data from single-cell RNA sequencing experiments. Uses a C++ backend with thin R wrappers to enable analysis of large-scale single-cell datasets. The package supports multiple data modalities including count matrices, paired data (splicing, RNA velocity, CITE-seq), and binary indicators. It implements a latent variable model with block coordinate descent optimization for dimensionality reduction and batch effect correction. Core algorithms are described in Madrigal et al. (2024) <doi:10.1038/s41467-024-50963-0>.
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human-cell-atlassingle-cell-genomicssingle-cell-rna-seqcppopenmp
4.48 score 4 stars 1 scripts 433 downloads
