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Overview
SeqGeq™ v1.6 Software is a device-agnostic desktop bioinformatics platform designed for the analysis of single-cell experiments and developed by the makers of FlowJo™ Software. SeqGeq™ Software includes a wide suite of informatics features including: V(D)J analysis, Seurat clustering, Monocle trajectory inference and much more.
SeqGeq™ Software allows researchers to perform advanced analysis, data exploration and visualization with an easy-to-use drag-and-drop interface familiar to anyone who uses FlowJo™ Software. SeqGeq™ Software generates quality figures that are easily shared for publication and collaboration.
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FEATURES
SeqGeq™ Software has an intuitive drag-and-drop interface and lets you:
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- Easily import your scRNA-seq data from any platform
- Perform dimensionality reduction with tSNE, PCA and LDA
- Select populations of interest using intuitive gating tools
- Identify, compare and contrast differentially expressed genes
- Generate publication-ready figures using powerful visualization tools
Powerful tools help you dive deep into single-cell gene expression
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- Differential expression analysis in volcano plots allows statistically rigorous exploration of up- and downregulated genes
- Gene set enrichment analysis—to define biological function and identify target genes of interest
- Quality control, which creates QC parameters used to remove outliers, debris and doublets
- More tools including those with which to map developmental trajectory, handle dropouts and categorical variables, and many more available as plugins on the FlowJo Exchange
Open-ended plugin architecture helps your research stay ahead of the curve. SeqGeq™ Software offers plugins that help bring informatics innovation to you quickly and intuitively. Current offerings include but are not limited to:
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- Seurat
- ViolinBox
- BatchLR
- TriMap
- iCellR
Download and see the complete library of plugins available on the FlowJo Exchange!
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NEW UPDATES
The latest release of SeqGeq™ v1.6 Software
- 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 available for export and publication.
- High-Resolution Figures—up to 4096 x 4096 pixels—are now available. This will make your figures for publication pop in a way never possible. In addition, the seed for contour plots is now adjustable to better illustrate populations of any size within that plot type.
- Dot Shapes can be adjusted within dot plots and dot plot overlays in the Layout Editor. Dot Sizes are also now editable on a layer-by-layer basis within the overlays.
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