Rxivist logo

projectR: An R/Bioconductor package for transfer learning via PCA, NMF, correlation, and clustering

By Gaurav Sharma, Carlo Colantuoni, Loyal A Goff, Elana Fertig, Genevieve Stein-O’Brien

Posted 06 Aug 2019
bioRxiv DOI: 10.1101/726547 (published DOI: 10.1093/bioinformatics/btaa183)

Motivation: Dimension reduction techniques are widely used to interpret high-dimensional biological data. Features learned from these methods are used to discover both technical artifacts and novel biological phenomena. Such feature discovery is critically import to large single-cell datasets, where lack of a ground truth limits validation and interpretation. Transfer learning (TL) can be used to relate the features learned from one source dataset to a new target dataset to perform biologically-driven validation by evaluating their use in or association with additional sample annotations in that independent target dataset. Results: We developed an R/Bioconductor package, projectR, to perform TL for analyses of genomics data via TL of clustering, correlation, and factorization methods. We then demonstrate the utility TL for integrated data analysis with an example for spatial single-cell analysis. Availability: projectR is available on Bioconductor and at https://github.com/genesofeve/projectR.

Download data

  • Downloaded 752 times
  • Download rankings, all-time:
    • Site-wide: 44,628
    • In bioinformatics: 4,643
  • Year to date:
    • Site-wide: 70,492
  • Since beginning of last month:
    • Site-wide: 98,369

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide