Analysis of neutrophil metabolic activity during metastasis using single-cell RNASeq and COnstraint-Based Reconstruction and Analysis.
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Updated
Mar 12, 2021 - HTML
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
Prediction of surface protein expression from mRNA expression using a regression auto-encoder neural network.
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.
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)
CD24 CART single cell analysis
Diary to a single cell RNA sequencing analysis using publicly available data
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.
Package for analyzing batch effects in single cell RNA sequencing (scRNA-seq) analysis and predicting their impact on downstream analysis.
Analyzing batch effects in single cell RNA sequencing (scRNA-seq) analysis and predicting their impact on downstream analysis.
Documentation analysis and manuscript figures
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