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CITATION.cff
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: sPARcRNA_Viz
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Mahitha
family-names: Simhambhatla
email: [email protected]
affiliation: University of Texas at Austin
orcid: 'https://orcid.org/0009-0004-1527-5864'
- given-names: Raina
family-names: Patel
email: [email protected]
affiliation: University of Texas at Austin
orcid: 'https://orcid.org/0009-0000-5129-4334'
- given-names: Mihir
family-names: Samdarshi
affiliation: Stanford University
email: [email protected]
orcid: 'https://orcid.org/0000-0002-2316-453X'
- given-names: Ayla
family-names: Bratton
email: [email protected]
orcid: 'https://orcid.org/0009-0004-4518-8593'
affiliation: University of Central Florida
- given-names: Sanjay
family-names: Soundarajan
email: [email protected]
orcid: 'https://orcid.org/0000-0003-2829-8032'
affiliation: California Medical Innovations Institute
- given-names: Vardaan
family-names: Bhat
email: [email protected]
identifiers:
- type: doi
value: 10.5281/zenodo.13308297
abstract: >-
sPARcRNA_Viz is an all-in-one gene expression visualization
utility integratable with o²S²PARC. Using sPARcRNA_Viz,
researchers can create an interactive t-SNE from
single-cell RNA-sequencing data, as well as perform in
silico GSEA analysis to determine the most highly
expressed genes. From these statistically significant
genes, researchers can determine potential gene ontologies
arising from their sample(s). In addition, the seamless
integration of sPARcRNA_Viz with the o²S²PARC computing
platform enables data accessibility concordant with FAIR
Data Principles.
keywords:
- single cell RNA
- differential gene expression analysis
- tSNE
- GSEA
license: MIT
version: 1.0.0
date-released: '2024-08-12'
doi: 10.5281/zenodo.13308297