A comprehensive multi platform software for microarray data analysis
Genowiz™ is a powerful gene expression analysis program that has been designed to store, process and visualize gene expression data efficiently. It includes a suite of advanced analysis methods from which researchers can select appropriate analysis methods for their dataset.
Genowiz™ allows researchers to organize experimental information (MIAME), import data files quickly and easily, work simultaneously with multiple experiments, import gene annotation files, pre-process and normalize data, perform cluster analysis, classify and view gene information, perform functional classification and track down intricate correlations in data by performing pathway analysis. All analysis performed is saved in database and can be retrieved as required.
Ten great reasons to try Genowiz™:
- Proven and Appreciated by Life Scientists:Genowiz™ has been used to study plant. Prokaryotic, Eukaryotic and clinically relevant microarray expression data.
- Easy to learn: User-friendly organization of features, GUIs and visualization tools which provide knowledge rather information.
- Validated Results: Accurate expression results validated against gold standards like R-package.
- Microarray platform independent:Supports all proprietary and open data formats e.g. Affymetrix, Aglilent. Also upload unique formats using customized uploader.
- Comprehensive Statistical and Bio-Analysis:All major Golden Goose Records Solde Normalization , Golden Goose Schuhe Sale Clustering, Classification well integrated with GO, Pathways and Gene Lists comparisons.
- Save time on analysis:Using built-in or user designed AutoGuide workflow module.
- Affordable Price:ust pay once! Perpetual Licensing.
- 24 X 5 Free Support:Free Live web demonstration and post sale e-mail support for the life.
- Consultative approach of Development:We continuously improve the software based on the latest scientific developments and your feedback.
- Upgrade Price:First year upgrade free. Minimal Upgrade fee thereafter and Dedicated support contract(Optional).
- Data transformation options such as imputation of missing values, log transformations, mean/median, Z-transformation, subtract control, divide by control, and scaling.
- Normalization techniques such as normalization for dye swap replicates, cDNA raw data normalization options (cDNA Loess and Print tip Loess) and quantile normalization. Separate normalization techniques are provided for cDNA and Affymetrix arrays. Normalization can be done using all genes or control genes.
- Filter data based on replicate samples, fold change, mean, standard deviation, calls and missing values. Replicate samples are handled using various parametric/non-parametric tests like Two Way ANOVA, Mann Whitney U Test, Kruskal Wallis Test, and One Sample t-Test. Multiple testing correction options like Bonferroni/FDR can be applied to reduce false positives.