Samuel Marsh - Associated Personnel

Samuel Marsh

Associated Personnel

Boston, Massachusetts, United States

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Summary

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Senior

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Samuel Marsh is a postdoctoral neuroimmunologist and associated personnel at Boston Children's Hospital/Broad/Harvard with eight years of experience applying single-cell genomics, proteomics, and ELISA to uncover mechanisms and biomarkers in neurodegenerative disease. He led development and validation of optimized wet-lab protocols for microglia and CSF immune cell processing—work that identified artifactual transcriptional signatures and culminated in a Nature Neuroscience methods paper. Comfortable at the bench and at the command line, he also develops open-source R tools (scCustomize) and contributed visualization improvements to the widely used Seurat package. His work uniquely spans living-patient CSF/blood cohorts and post-mortem/acute brain tissue, and he has translated those technical advances into novel biomarker assays and a discovered CSF immune cell population enriched for Alzheimer’s risk.

8 years of coding experience

3 years of employment as a software developer

Bachelor of Science (B.S.), Behavioral Neuroscience, Bachelor of Science (B.S.), Behavioral Neuroscience at Northeastern University

Doctor of Philosophy (Ph.D.), Neurobiology & Behavior, Doctor of Philosophy (Ph.D.), Neurobiology & Behavior at University of California, Irvine

Stackoverflow

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Github Skills (8)

data-visualizations10

rna-seq10

data-visualization10

data-visualisation10

ggplot10

r10

cran9

bioinformatics8

Programming languages (6)

RC++CSSHTMLWDLPython

Github contributions (5)

satijalab/seurat

Aug 2020 - Apr 2022

R toolkit for single cell genomics

Role in this project:

Data Scientist

Contributions:31 commits, 38 PRs, 1195 comments in 1 year 8 months

Contributions summary:Samuel primarily contributed to the `seurat` R package, focusing on enhancing the visualization capabilities for single-cell genomics data. Their contributions included adding features like "do.shuffle" to the `DimPlot` function and expanding the functionality of `FeaturePlot` by introducing parameters such as `keep.scale` and `raster`. Further, they updated and refined existing functions like `CellCycleScoring`, addressing typos and documentation for improved usability and clarity.

single-cell-genomicscranhuman-cell-atlasgenomicsbioinformatics

samuel-marsh/scCustomize

Sep 2021 - Jan 2023

R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.

Contributions:15 releases, 1247 commits, 42 PRs in 1 year 3 months

visualizationsingle-cell-genomicsr-packageggplot2seurat

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