GeneSifter® Analysis Edition:
Identifying Biological Significance

To understand the biology underlying complex expression patterns in microarray data, you must determine both the statistical and biological significance. GeneSifter’s unique ease-of-use enables you, the scientist, to explore the statistically significant interplay of your data with factors of biological relevance.

Update: Geospiza is pleased to announce the winter release of GeneSifter Analysis Edition. The most recent release features splice index analysis and base variant calling for Next Generation Sequencing as well as enhanced support for Affymetrix miRNA and Exon/Gene ST arrays. View the Product Brief (PDF) for more information.

Unparalleled Ease-of-Use
GeneSifter offers award winning ease-of-use, enabling you to understand the biological significance of your data and draw meaningful conclusions quickly.

Within this easy-to-use analysis platform, you can produce comprehensive reports for over 30 types of validated data analysis techniques. Or, for fast results, you can use our One-Click Gene SummaryTM merging the latest annotation from 11 independent sources.

Sophisticated Statistical Analysis
Combined with its unique ease-of-use, GeneSifter offers a robust statistical framework with 15 advanced options, including 2-way ANOVA, PCA, PAM, hierarchical clustering, CLARA, FDR, FWER, RMA, Max T and more.

Through a web-based interface, GeneSifter provides “R” platform biostatistics and Integrated Gene Ontology and pathways analysis. For validation, MIAME-compliant protocols are also available.

Anytime, Anywhere Access
GeneSifter provides its product through a secure web-based interface, offering convenience and performance. Keep your data secure with password protected access to your individual account or opt to share your findings worldwide through web-based collaboration - the choice is yours.

GeneSifter takes care of your data security and management with its state-of-the-art hosting facility and daily back-ups of your critical data.

Focus on the science, not the software with the tools you need to understand the data:

• Pairwise Analysis
  Define two groups then apply normalization, statistical analysis and quality metrics to create lists of differentially expressed genes.
• Filtering
  Apply fold change cutoffs, statistical analysis and quality metrics to create lists of differentially expressed genes.
• Interactive Scatter Plot
  Provides visualization of the entire array data set and identification of individual genes.
• Cluster Samples
  Use hierarchical clustering to determine the relationship of samples based on a gene list.
• Project Analysis
  Define and analyze groups across multiple conditions.
• Function Navigation
  Rapidly identify and group genes based on function using Gene Ontology terms.
• Ontology Report
  Summarize the ontology terms for a gene list or use Z-Scores to assess biological significance.
• Pattern Navigation
  Define and identify patterns of gene expression with supervised clustering.

Contact us for more information or to find out how Geospiza can help with your analysis or lab automation. 877.Web.Gene or info@geospiza.com or Request More Info