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nDSPA

An R package for quality metrics, preprocessing, visualization, and differential testing analysis of spatial omics data

Tutorial: https://github.com/riyuebao/nDSPA/wiki/Tutorial

Documentation: https://github.com/riyuebao/nDSPA/wiki/Documentation (under construction)

Short demo for the Rshiny app: https://bit.ly/3jpQh3e

Installation

To start using nDSPA.

  • To launch the R shiny app on website:
  1. Go to https://riyuebao.shinyapps.io/ndspa/

  2. Start using nDSPA!

  • To launch the R shiny app locally:
  1. download the software from github repository: git clone [email protected]:riyuebao/nDSPA.git

  2. navigate into the nDSPA directory on your computer

  3. within the nDSPA directory, open app.R in Rstudio

  4. once app.R is open in Rstudio, click Run App button on the top right corner

  5. bravo! you are there

  • To start using command line functions:
  1. download the software from github repository: git clone [email protected]:riyuebao/nDSPA.git

  2. navigate into the nDSPA directory on your computer

  3. source global.R

nDSPA is under rapid development. Options might change between versions!

Version history

2020.08.28 Version 0.2a

  • Added analysis and stats modules for data generated on NanoString DSP platform
  • Added spatial expression map
  • Added simulated test files

Future development

  • Add multi-segment selection in QC and Normalization module
  • Add R package support
  • Add analysis modules and test files for data generated on Vectra mIF imaging platform

Funding support

UPMC Hillman Cancer Center, supported in part by NCI through the UPMC Hillman Cancer Center CCSG award (P30CA047904).”

Acknowledgment

We acknowledge contribution from our colleagues and friends in pushing nDSPA to fuition:

  • We thank Shelley Reynolds and Ernest M Meyer (UPMC Flow Cytometry Core) for processing the samples and producing the data that were used to generate the syntethic datasets provided in nDSPA.
  • We thank Aditi Kulkarni (UPMC Hillman Cancer Center), Kyle Hernandez, Tzuni Garcia and Lei Huang (University of Chicago) for helping test and verify the software.

Cite us

Rajesh Acharya, Tullia Bruno, Jason J Luke, and Riyue Bao. nDSPA: An R package for quality metrics, preprocessing, visualization, and differential testing analysis of spatial omics data. Link: https://github.com/riyuebao/nDSPA

Contact us

Please reach out to us by emails, leave us a message here, or find us on twitter!

Issues or questions

Please submit a ticket on GitHub issues.