DNASTAR ArrayStar QSeq module

Category Cross-Omics>Next Generation Sequence Analysis/Tools and Genomics>Gene Expression Analysis/Profiling/Tools

Abstract The QSeq module of ArrayStar v3.0 permits quantitization of gene expression levels along with visualizations that are part of ArrayStar.

This ability to quantitize transcriptomes using 'Next Generation sequencing' techniques allows researchers to measure presence and levels of transcripts from known and newly discovered genes faster and on a larger scale than previously was possible.

RNA-Seq Analyses --

RNA-Seq is a technique that involves direct sequencing of cDNAs using high-throughput, Next Generation sequencing technologies to permit transcription levels from a particular genomic region to be quantified from the density of corresponding reads.

RNA-Seq provides users with several advantages over conventional microarray applications. While the field of coverage with microarrays is limited by the probe density of the array, RNA-Seq provides a more comprehensive view of the transcriptome.

In addition to this, because of the deep sequencing capability with Next Generation sequencing, RNA-Seq can provide better information on low abundant genes and their expression profiles since it is limited only by the number of reads generated.

Several Next Generation sequencing manufacturers provide users the ability to generate such data. ArrayStar v3.0 provides a wide range of analytical and visualization tools that will assist researchers in analyzing this data.

Data files from Illumina®, Roche 454® and Helicos™ can be directly read.

RNA-Seq Applications include:

1) Transcript Discovery and Mapping.

2) Detection of alternative splicing.

3) Transcriptome quantitization.

The QSeq module of ArrayStar v3.0 permits quantization of gene expression levels along with a wide range of visualizations.

Graphic capabilities of ArrayStar that are helpful in RNA-Seq data analysis include:

1) Heat Maps (see below...).

2) Line Graphs (see below...).

3) Scatter Plots (see below...).

Heat Maps --

1) Heat Maps illustrate expression levels of the genes across a number of experiments.

2) Genes can be selected within the Heat Map for additional analysis.

3) The Gene Tree to the left of the Heat Map reveals a sub-tree of genes.

4) Clicking on branches reveals cluster information.

5) Gene Ontology (GO) information is easy to obtain by passing your cursor over any gene name or Heat Map location.

6) Selection of genes or gene clusters in the Heat Map is shown in the expression level histogram in gray and illustrates relative expression levels.

Line Graphs --

ArrayStar’s Line Graph view plots the expression levels for selected genes over each experiment in your project, and connects the data points with a line so that expression levels are shown relative to one another across the group of experiments.

Expression levels are plotted vertically along the Y-axis, while the X-axis position for each point is determined by the experiment to which it belongs.

Advantages to this system are:

1) Provides an easy visual indication of expression level changes over the course of the experiment.

2) Provides a quick visualization of relative changes of different genes over the course of the experiment.

Scatter Plots --

ArrayStar’s Scatter Plot view gives a visual comparison of gene expression levels between any two datasets; whether they are individual arrays or replicated sets.

Each data point on the Scatter Plot represents an individual gene and is plotted based on its expression level in both of the selected experiments.

Data can be scaled and visualized as either linear or log2 values.

Specific groups of genes of interest can be targeted easily. Gene groups do Not necessarily need to be adjacent on the plot to be selected. Selected genes are indicated in a Scatter Plot view by being white in color.

Three solid green lines are drawn diagonally across the scatter plot. The middle green line is the identity line, or the x=y line. Data points on this line represent genes that are expressed at the same level in both datasets.

The other two lines delineate genes with at least a two-fold change in intensity value in one of the datasets.

The dashed purple line on the scatter plot is the linear regression or “best-fit” line, a line that passes as near to as many data points as possible.

Each data point is colored to reflect where it is in comparison to the x=y line. The colors for data points, as well as the fold lines and regression line can be changed to match your preferences.

Note: QSeq is an optional module that can be purchased with ArrayStar v3.0 (see G6G Abstract Number 20058A).

System Requirements

ArrayStar (Windows® computer running XP or Vista™)

Projects containing large data sets may require additional computing capacity.


Manufacturer Web Site DNASTAR ArrayStar QSeq module

Price Contact manufacturer.

G6G Abstract Number 20375

G6G Manufacturer Number 100770