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 |