PCAworkshop
importedsoftware/pcaworkshop
An introduction to matrix factorization and PCA and SVD.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- aedin.github.io/PCAworkshop/
- Repository
- github.com/aedin/PCAworkshop
- Documentation
- unknown
- Tags
- correspondence-analysis · dimensionality-reduction · exploratory-data-analysis · pca · principal-component-analysis · single-cell · singular-value-decomposition · svd
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- OpenLimbTTpca · principal-component-analysis
An Open-Source, synthetic transtibial residual limb anatomic dataset
- neurosynth_semantic_mapcorrespondence-analysis
A repository for "The Latent Semantic Space and Corresponding Brain Regions of the Functional Neuroimaging Literature" -- http://www.biorxiv.org/content/early/2017/07/20/157826
- BadranSeqpca · single-cell
The scRNA-seq figures your paper deserves. One package, zero boilerplate.
- cshl-singlecell-2017pca · single-cell
Single Cell Analysis course at Cold Spring Harbor Laboratory 2017
- pySTATISprincipal-component-analysis
Python implementation of STATIS for analysis of several data tables
- kanaexploratory-data-analysis · single-cell
Single cell analysis in the browser
- api.github.com/repos/aedin/PCAworkshopretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-09-28, 41 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/6.json→ .entries["pcaworkshop"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.