pagoda2
too-many-cells
pagoda2 | too-many-cells | |
---|---|---|
2 | - | |
191 | 100 | |
2.1% | - | |
5.3 | 4.5 | |
2 months ago | 5 months ago | |
JavaScript | Haskell | |
- | GNU General Public License v3.0 only |
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pagoda2
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GOterm analysis in Seurat
Try pagoda2 for this: https://github.com/kharchenkolab/pagoda2
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Seurat Vs Pagoda2 For Scrnaseq Analysis
I realize that this is a bit old, but I find pagoda2 faster: https://github.com/kharchenkolab/pagoda2
too-many-cells
We haven't tracked posts mentioning too-many-cells yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
seurat - R toolkit for single cell genomics
subsample - Subsample data from a uniform distribution so two different statuses for the same entity have the same number of samples.
scanpy - Single-cell analysis in Python. Scales to >1M cells.
collapse-duplication - Process the output of heatitup in order to collapse sequences into clones by similar ITD mutations.
kana - Single cell analysis in the browser
integreat - Integrate difference data sources and optionally perform differential integration.
alevin-fry - 🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.
normalize - normalize
heatitup-complete - Find and annotate ITDs with assembly or read pair joining using suffix trees and characterize the exogenous segments within the spacer using heat diffusion. A layer on top of heatitup for additional functionality such as working with BAM files directly.
tex-join-bib - Compile separate tex files with the same bibliography.
BiobaseEnsembl - Ensembl related functions and datastructures
birch-beer - Generate a tree for displaying a hierarchy of groups with colors, scaling, and more.