2 Works

EcoTyper: a machine learning framework for large-scale identification of cell type-specific transcriptional states and cellular ecosystems

Bogdan-Alexandru Luca, Chloé Steen, Armon Azizi, Andrew Gentles, Arash Ash Alizadeh & Aaron Newman
EcoTyper is a machine learning framework for large-scale identification of cell type-specific transcriptional states and their co-association patterns from bulk, single-cell, and spatially resolved gene expression data. EcoTyper performs the following major steps: 1) In silico purification: This step enables imputation of cell type-specific gene expression profiles from bulk tissue transcriptomes, using CIBERSORTx (Newman et al., Nature Biotechnology 2019). 2) Cell state discovery: This step enables identification and quantitation of cell type-specific transcriptional states. 3)...

T cell characteristics associated with toxicity to immune checkpoint blockade

Alexander X Lozano, Aadel A Chaudhuri, Aishwarya Nene & Aaron M Newman
A supplementary resource for “T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma”.

Registration Year

  • 2021
    2

Resource Types

  • Interactive Resource
    2

Affiliations

  • Stanford University
    2
  • University of Washington
    1
  • Yale University
    1