SeqGeq™ v1.6 [seek-geek] analyzes gene expression data—particularly from single-cell RNA sequencing—and will help you cluster and subset populations of cells, navigate this data stream using gene sets, and rapidly produce reports and visualizations.

Getting Started? Click Here!

Getting Started with SeqGeq™

 SeqGeq™ (SEEK-GEEK) analyzes gene expression data particularly from single-cell RNA sequencing (scRNA-seq) and will help you cluster and subset populations of cells, navigate this data stream using gene sets, and rapidly produce reports and visualizations. Stay tuned for upcoming training resources!

Advanced SeqGeq Training

Follow along with Director of Product Innovation Ian Taylor In this series of advanced SeqGeq webinars on four major lessons in SeqGeq: quality control, dimensionality reduction, clustering, and DEG analysis. 

Combining scRNA-seq and Flow Analyses

Example analysis of single-cell protein expression, and whole transcriptome in a combined data matrix.

Differential Expression Analysis

Introduction to finding Differentially Expressed GeneSets between populations of interest using SeqGeq's volcano plots.

GeneSet Enrichment Analysis

Making sense of differentially expressed GeneSets from known and unknown populations using GeneSet Libraries.

Genomic Cytometry

"Genomic Cytometry: Using Multi-Omic Approaches to Increase Dimensionality in Cytometry" was an Invited Tutorial given at the 2019 CYTO conference for the the International Society for the Advancement of Cytometry on the 22nd May 2019. 

This tutorial will begin by explaining why the emerging field of Genomic Cytometry, i.e. the measurement of cells using genomic techniques (e.g. sequencing), in conjunction with more traditional cytometry techniques such as fluorescence, mass and imaging cytometry is becoming a standard tool for biologists looking to unravel complex cellular processes and to develop a deeper understanding of heterogeneity.