SeqGeq dCODE Dextramer


 SeqGeq dCODE Dextramer® (RiO) analysis walkthrough  This is a step-by-step guide to perform the analysis of a dCODE Dextramer® (RiO) and AbSeq dataset in SeqGeq v1.6. This resource guide will help you perform a standard manual gating analysis or an unbiased analysis based on your desired approach. You can read the process below or download it as… Read more »


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Introduction PhenoGraph is a clustering algorithm that robustly partitions high-parameter single-cell data into phenotypically distinct subpopulations. First, it constructs a nearest-neighbor graph to capture the phenotypic relatedness of high-dimensional data points and then it applies the Louvain graph partition algorithm to dissect the nearest-neighbor graph into phenotypically coherent subpopulations. The PhenoGraph algorithm has been implemented… Read more »

Plugin Demonstration Videos


Plugins add a wealth of features to SeqGeq, and in doing so compliment its rich base of native analysis functionality. These plugins can be downloaded from the FlowJo Exchange on our website. The SeqGeq plugins are constantly being updated with new tools designed by the research community, allowing users to stay on the cutting edge of analysis. Each plugin may have slightly… Read more »

1.6.0 Release Notes


Highlights Mouse-Over Information shown for both cells and genes within Graph Windows. This means that researchers can now very quickly determine the identity of individual dots in their plots with ease. We’ve also added the ability to “pin” the parameter names in GeneView plots to graphs within the Layout Editor, so that these annotations become… Read more »

Mouse-Over Annotations


SeqGeq v1.6 and beyond now contains a mouse-over annotations feature for individual dots per cell, sample (for bulk sequencing), or per gene.     Simply drag your cursor over the plot in a Graph Window in order to see the names of dots displayed there as tool-tips. In addition to the mouse-over information, right click… Read more »



Overlays give researchers a powerful way to visualize comparisons between populations. On a parameter by parameter basis in univariate histograms, by binning two histograms together to reveal a bivariate dot plot, or even applying machine learning to generate derived parameters representing embedded space in a single plot. (such as tSNE and UMAP) Univariate Traditional univariate… Read more »

1.5.0 Release Notes


Highlights Introducing a Normalization Platform – Now available in the Discovery band of the Workspace, which allows researchers to run normalization across parameter-sets in data matrices. Multi-Geneset Enrichment Analysis – Simply select multiple genesets and run the enrichment platform against a geneset library (GMT) of your choice. Opt-SNE (1) algorithm enabled! This means researchers won’t usually need to… Read more »



  Intro Normalization is an important consideration for any analysis, and is common to include in many sequencing datasets. Performing normalization will generate a new icon meant (generically) to indicate that an adjustment has been applied, moving (or reshaping) data:   Within the normalization platform different lists of parameters can be added. Adding a new… Read more »

VDJ Explorer


Background Variable (V), diversity (D), and joining (J) regions of lymphocyte immune cell receptor proteins are capable of undergoing recombination, which produces a set of unique alpha and beta chain pairs (aka clonotypes), the sum totality of which is sometimes called the repertoire of T and B cell populations. Measurements of clonotype diversity give researchers… Read more »

Basic Tutorial


SeqGeq Basic Tutorial (SeqGeq v1.6.0) This tutorial is designed to give researchers a basic overview of the features and functions available in the SeqGeq bioinformatics analysis platform. All data files illustrated here are available as demo data included in the installation of SeqGeq. Specifically, analyses illustrated here will focus on the 6K_PBMC.csv data file. *Analysis… Read more »