Quality Control

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Quality control (QC) in single cell RNA sequencing is extremely important at every stage of the workflow. Researchers are well aware of this concern and may have conducted various types of QC upstream of their analysis in SeqGeq. For those that haven’t yet, or those that want to refine or simply illustrate their QC in… Read more »

Differentially Expressed Gene Filtering

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There are many ways to assess the differential expression of genes (DEG) between populations of single cells – Here we detail some of the methods available for researchers using SeqGeq. Currently Volcano plots are the only truly statistically rigorous method of performing DEG analysis in SeqGeq. A volcano plot is named for the shape of… Read more »

Vector Inspector

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The Vector Inspector allows you to apply the same dimensionality reduction parameters (DRPs) to new samples, to see the weight of parameters comprising DRPs, and to export those parameters as gene sets.   Vectors DRPs such as LDA or PCA are new combinations of parameters whose contribution is weighted differently. The combined amount or “weight” of these… Read more »

Rank and Quantile Plots

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Rank and quantile plots are important graph types for single cell RNA-sequencing analyses, which facilitate certain quality control filters.   What are these Plot Types? A rank plot simply places events in descending order, with regard to values on the currently chosen y-axis. Similarly a quantile plot places events in ascending order, with regard to… Read more »

1.2.0 Release Notes

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Highlights Introducing a Quality Control button yielding QC parameters in both Cell and Gene Views within the Graph Window. Volcano Plots available from Gene View, for calculating statistically significant Differentially Expressed Genes. Dimensionality Reduction Parameter Vector Inspector platform. Added Rank and Quantile plot types.   Improvements Enhanced performance. Searchable parameter selector within the Add Statistics… Read more »

1.1.0 Release Notes

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Highlights Major improvements & bug fixes from SeqGeq v1.0.1 Plugin API feature. Initial plugins are available on The FlowJo Exchange. Improvements Enhanced performance Support for HDF5 (.h5) formatted data files Color mapping key for plots in layouts Support for Plugins New and improved demo data file for Melanoma data matrix from Tirosh, et al. Fixes tSNE run… Read more »

Error Messaging

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Sometimes SeqGeq will inevitably fail to complete some tasks or to perform some function, especially for researchers who regularly push the envelope. In these cases we try to include error messaging that conveys the issue(s) at hand in an informative and actionable way. Here are a list of common errors and a brief description of… Read more »

PBMC Tutorial

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SeqGeq provides a wide assortment of tools for the single cell RNA-Sequencing (scRNA-Seq) researcher and/or data analyst. Here we detail one possible workflow, using a particular PBMC expression matrix as an example. Please note, the direction of this workflow is linear for simplicity’s sake, not due to any constraints of the software. Though many users will likely… Read more »

Seurat

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Seurat is an extremely popular pipeline for analyzing single cell RNA Sequencing (scRNA-Seq) data developed and maintained by the Satija lab.(1) We’ve implemented this tool as a plugin in SeqGeq in order to make the features there available for our users and simplify the process of producing results from the Seurat pipeline as simple as possible…. Read more »

AutoCatGate

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The Automatic Categorical Gating (AutoCatGate) plugin can be used to quickly and conveniently create gates on parameters with discrete values. All of FlowJo, LLC’s plugins are hosted on and available for free download on The FlowJo Exchange.   Background Parameters with discrete values include: “SampleID”, “Subject”, “AnimalModel”, “Cluster#”, etc. These parameters can be entered manually as… Read more »