Aligning Science Across Parkinson's Logo Text

Key Resource Table for Multi-omics machine learning classifier and blood transcriptomic signature of Parkinson’s disease

By Ruifeng Hu, Xianjun Dong, PhD
View Published Dataset

Output Details

Description
Key resource table related to the publication Multi-omics machine learning classifier and blood transcriptomic signature of Parkinson’s disease.
Identifier (DOI)
10.5281/zenodo.21937994
Tags
  • Key Resource Table
Discovery Team
Team Scherzer
Program
Collaborative Research Network
Theme
PD Functional Genomics

Meet the Authors

Related Research

Key Resource Table for the paper “Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data”

The key resource table to go with the publication "Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data" by Simmons et al.

View Dataset

Key Resource Table related to Maor et al., 2023: α-Synuclein Promotes Neuronal Dysfunction and Death by Disrupting the Binding of Ankyrin to β-Spectrin

Key resource table related to the publication: Maor et al., 2023. α-Synuclein Promotes Neuronal Dysfunction and Death by Disrupting the Binding of Ankyrin to β-Spectrin

View Dataset

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq Data

We systematically investigated experimental and computational design choices for their effects on allelic imbalance analysis in droplet-based snRNA-seq data from human samples. We show that many factors, including read length, sequencing technology,

View Article
View More Outputs
Aligning Science Across Parkinson's
Powered by  GDPR Cookie Compliance (opens in a new tab)
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.