# Posts

## SAS 9.2 Graphics Course

Here is a SAS 9.2 Graphics Course and the code which shows you how to use the SGPLOT, SGPANEL, SGSCATTER, SGRENDER, and Graph Template Language to produce high quality graphs with simple code.

## Array Studio 4.0 is released

**The major improvements in Array Studio 4.0:**

**1. NGS support**: they developed workflows for DNA-seq, RNA-seq and MiRNA-seq. The workflows include our high performance alignment modules (works for both single end and paired end) and many downstream analysis. For oncology users, we also developed the full gene fusion modules for both single-end and paired end modes. Papers and white papers on NGS are available upon request for existing users.

**2. Visualization improvements**: flip x/y axis for almost all views, better PowerPoint exporting, improved performance for filtering, 4 new views for -omic data and many other features

**3. Statistics improvements:**trend test, bootstrap for two-group tests, improved one-group test, automatic GeneCard links and many other features

**4. -Omic platform support:**Nanostring, Nimblegen, Mascot integration, improved Agilent support, improved Affymetrix support for presence/absence, and many other features

**5. Project/analysis management:**automatically records logs for all analysis, allow users to pause/resume any analysis, improved progress dialog, and many other features

**6. Single user guide file:**thy now provide a ~670 page user guide PDF file (Help | User Guide) in addition to the previous context-sensitive PDF pages. This user guide covers every aspects of the software.

## Jitter Scatter Plot with Boxplot overlaid SAS

Jitter Scatter Box and Boxplot overlaid SAS Macro

These days customers are more demanding when it comes to graphs, and want to obtain a lot of information fast from a single graph. There’s been a lot of interest on overlaying a Boxplot on top of a Scatter Plot, and there was no easy way to do that with the Scatter and Vbox Statements in Proc SGPLOT, let along producing a jittered scatter plot. The boxplot is produced by cleverly using the Vector statement in SGPLOT. Hope the code helps!

## Adding Jitter to SG Procedures in SAS

## ROC Hard? No, ROC Made Easy! – Award Winning SAS Student Ambassador Paper

A ROC (Receiver Operator Characteristic) curve shows how well two groups are separated by plotting the Sensitivity by 1 – Specificity. When used alone, the cut off used to balance the desired Sensitivity and Specificity is not shown. Furthermore the ROC curve does not display the interesting counts and percentages of the True Positives, True Negatives, False Positives, and False Negatives.

The macro presented in this paper uses Graph Template Language (GTL) and the Statistical Graphics Engine (SGE) to quickly and easily create an informative graph that can be edited and which displays the Sensitivity and Specificity of your binary classifier. The macro also displays scatter and box plots of the desired variable by the binary classifiers to identify unusual results. Options also display a confusion matrix and area under the curve (AUC) results. The confusion matrix is calculated from the default Sensitivity and Specificity intersection, but the cut off can be made explicitly. The AUC statistic shows how well the binary classifier discriminates. This macro is used with SAS® 9.2 Phase 2.

## Plotting Foldchanges and (95%) confidence intervals in SAS 9.2

The following SAS 9.2 tip plots the foldchange and (95%) confidence intervals, and displays the foldchange on the graph.

Plotting Foldchanges and (95%) confidence intervals in SAS 9.2

## Power graphs with cross reference in SAS

The following SAS tip plots power curve’s and cross references the sample size per group required to achieve the power.

## Traffic Lighting p-Values in SAS

The following SAS tip formats the rows outputted to Excel in three different colors depending on the results of the p-values

## Generating Correlated Random Variables using SAS

The Powerpoint Presenation below and the SAS Code will explain and generate correlated random variables for you. It’s very useful when you have to produce correlated graphs!