STREAK: A supervised cell surface receptor abundance estimation strategy for single cell RNA-sequencing data using feature selection and thresholded gene set scoring

Azka Javaid; Hildreth Robert Frost

doi:10.1371/journal.pcbi.1011413

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Open Access

Peer-reviewed

Research Article

STREAK: A supervised cell surface receptor abundance estimation strategy for single cell RNA-sequencing data using feature selection and thresholded gene set scoring

Azka Javaid ,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: azka.javaid.gr@dartmouth.edu

Affiliation Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, United States of America

https://orcid.org/0000-0001-5325-1768

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Hildreth Robert Frost

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

Affiliation Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, United States of America
⨯

STREAK: A supervised cell surface receptor abundance estimation strategy for single cell RNA-sequencing data using feature selection and thresholded gene set scoring

Azka Javaid,
Hildreth Robert Frost

Published: August 21, 2023
https://doi.org/10.1371/journal.pcbi.1011413
See the preprint

About the Authors

Azka Javaid

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: azka.javaid.gr@dartmouth.edu

Affiliation Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, United States of America

https://orcid.org/0000-0001-5325-1768

Hildreth Robert Frost

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing

Affiliation Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, United States of America

Competing Interests

The authors have declared that no competing interests exist.

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Gene expression
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Algorithms
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Data visualization
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Monocytes
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Protein abundance
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Spleen
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Support vector machines
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Transcriptome analysis
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