hadge: a comprehensive pipeline for donor deconvolution in single cell
Curion, F.; Wu, X.; Heumos, L.; Andre, M. G.; Halle, L.; Grant-Peters, M.; Rich-Griffin, C.; Yeung, H.-Y.; Dendrou, C. A.; Schiller, H. B.; Theis, F. J.
Show abstract
Single cell multiplexing techniques (cell hashing and genetic multiplexing) allow to combine multiple samples, thereby optimizing sample processing and reducing batch effects. Cell hashing conjugates antibody-tags or chemical-oligonucleotides to cell membranes, while genetic multiplexing allows to mix genetically diverse samples and relies on aggregation of RNA reads at known genomic coordinates. We developed hadge (hashing deconvolution combined with genotype information), a Nextflow pipeline that combines 12 methods to perform both hashing- and genotype-based deconvolution. We propose a joint deconvolution strategy combining the best performing methods and we demonstrate how this approach leads to recovery of previously discarded cells in a nuclei hashing of fresh-frozen brain tissue.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Coralysis enables sensitive identification of imbalanced cell types and states in single-cell data via multi-level integration 96%
- QClus: A droplet-filtering algorithm for enhanced snRNA-seq data quality in challenging samples 95%
- Disentangling single-cell omics representation with a power spectral density-based feature extraction 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.