Lindseynicer
Post-doctoral Researcher, Shanghai Jiao Tong University School of Med affiliated Renji Hospital Co-creator of Youtube channel "Liquid Brain Bioinformatics"
Pinned Repositories
Analysing-10X-ScRNA-data-Wang-et-al-2020-Nat-Commun-
I redo the ScRNA analysis in the paper of Wang et al 2020, Nat Comm. Here's my modified script for Helen He Zhu github (https://github.com/HelenHeZhu/StemCell)
How-to-analyze-GEO-microarray-data
GSE analysis for microarray data, for the tutorial as shown in https://www.youtube.com/watch?v=JQ24T9fpXvg&t=947s
scRNAseq-analysis-walkthrough-Reproducing-analysis-of-Karthaus-et-al-Science-2020
Using non-negative matrix factorization (NMF), graph-based clustering, and XGBoost machine learning, we analyze time-series samples and identify cell types for each cluster. Discover how NMF uncovers patterns, graph clustering reveals relationships, and XGBoost predicts and classifies.
Somatic-mutated-genes-interaction
UMAP-
WGCNA_tutorial
A step-by-step tutorial for Weighted correlation network analysis (WGCNA)
Yu2021NaturePlants
Scripts for WGCNA network analysis and correlation with microbial taxonomy traits
Lindseynicer's Repositories
Lindseynicer/WGCNA_tutorial
A step-by-step tutorial for Weighted correlation network analysis (WGCNA)
Lindseynicer/How-to-analyze-GEO-microarray-data
GSE analysis for microarray data, for the tutorial as shown in https://www.youtube.com/watch?v=JQ24T9fpXvg&t=947s
Lindseynicer/Analysing-10X-ScRNA-data-Wang-et-al-2020-Nat-Commun-
I redo the ScRNA analysis in the paper of Wang et al 2020, Nat Comm. Here's my modified script for Helen He Zhu github (https://github.com/HelenHeZhu/StemCell)
Lindseynicer/Yu2021NaturePlants
Scripts for WGCNA network analysis and correlation with microbial taxonomy traits
Lindseynicer/Somatic-mutated-genes-interaction
Lindseynicer/UMAP-
Lindseynicer/scRNAseq-analysis-walkthrough-Reproducing-analysis-of-Karthaus-et-al-Science-2020
Using non-negative matrix factorization (NMF), graph-based clustering, and XGBoost machine learning, we analyze time-series samples and identify cell types for each cluster. Discover how NMF uncovers patterns, graph clustering reveals relationships, and XGBoost predicts and classifies.