starfish: scalable pipelines for image-based transcriptomics

Jupyter Notebook Python wdl Submitted 29 June 2020Published 04 May 2021
Review

Editor: @csoneson (all papers)
Reviewers: @giovp (all reviews), @shazanfar (all reviews), @vals (all reviews)

Authors

Shannon Axelrod, Matthew Cai (0000-0003-4998-6328), Ambrose J. Carr (0000-0002-8457-2836), Jeremy Freeman (0000-0001-7077-7972), Deep Ganguli, Justin T. Kiggins (0000-0002-4638-7015), Brian Long (0000-0002-7793-5969), Tony Tung, Kevin A. Yamauchi (0000-0002-7818-1388)

Citation

Axelrod et al., (2021). starfish: scalable pipelines for image-based transcriptomics. Journal of Open Source Software, 6(61), 2440, https://doi.org/10.21105/joss.02440

@article{Axelrod2021, doi = {10.21105/joss.02440}, url = {https://doi.org/10.21105/joss.02440}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {61}, pages = {2440}, author = {Shannon Axelrod and Matthew Cai and Ambrose J. Carr and Jeremy Freeman and Deep Ganguli and Justin T. Kiggins and Brian Long and Tony Tung and Kevin A. Yamauchi}, title = {starfish: scalable pipelines for image-based transcriptomics}, journal = {Journal of Open Source Software} }
Copy citation string · Copy BibTeX  
Tags

xarray skimage microscopy imaging biology single cell biology spatial transcriptomics MERFISH In Situ Sequencing osmFISH smFISH BaristaSeq dartfish starmap seqFISH

Altmetrics
Markdown badge

 

License

Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License

Table of Contents
Public user content licensed CC BY 4.0 unless otherwise specified.
ISSN 2475-9066