Analysis of neutrophil metabolic activity during metastasis using single-cell RNASeq and COnstraint-Based Reconstruction and Analysis.

TRIAGE is provided here as an R package comprised of three tools: 1) TRIAGEgene, 2) TRIAGEcluster, and 3) TRIAGEparser, along with a set of functions that streamlines creation of publication-ready figures and facilitates smoother data analysis.

diabetes

scripts for scRNA-Seq/scATAC-Seq

Analysis of Single-Cell RNA data from SRR14294834 in peripheral blood mononuclear cells in severe asthma

CD24 CART single cell analysis

Diary to a single cell RNA sequencing analysis using publicly available data

Prediction of surface protein expression from mRNA expression using a regression auto-encoder neural network.

All analysis performed during the generation of the manuscript "ICAT: A Novel Algorithm to Robustly Identify Cell States Following Perturbations in Single Cell Transcriptomes"

scMLnet2.0: Single-cell RNA-seq data-based inference of multilayer inter- and intra-cellular signaling networks

SBC analysis with DIGIST (In progress)

Nek2 single cell analysis

This project employs Scanpy in Python for analyzing spatial transcriptomics data, encompassing preprocessing, quality control, clustering, and marker gene identification, resulting in informative visualizations to reveal gene expression patterns and cellular interactions within tissue samples.

Single-cell sequencing is a novel technology to define intercellular heterogeneity, rare cell types, cell genealogies or disease evolution based on profiling thousands of cells in parallel. Identification of cellular subpopulations from heterogeneous populations of cells could be done by data clustering.

Deconvolution of bulk proteomics using scRNA-Seq

BIO 322 Cell Prediction project. By Simon Lee and Léa Goffinet

The functional analysis of genes provides relevant information to understand cellular function. Further, the mapping of genetic interactions sheds light on how genes act in the emergence of cellular complexity. Here, we present the most extensive genetic interaction and morphological profiling screen in a metazoan cell to date. We profiled 680 0…

Simple functions to create ggplot2 plots to visualize single cell expression data in 2D dimensionality reductions to avoid overplotting. Includes a wrapper for Seurat objects.

QuantQC is a package for quality control (QC) of single-cell proteomics data. It is optimized to work with nPOP, a method for massively parallel sample preparation on glass slides.