1. Intro into Qlucore 3.5 – new major release
2. Benefits of visualization-driven OMICs data analysis – using gene expression data from “Classification of pediatric acute lymphoblastic leukemia by gene expression profiling” Ross M, et al. We will explore this data using 3D PCA, heatmap, tSNE, box plot, etc; set up ANOVA and various ttest analyses, compare results with published gene expression signature, and (time permitting) will build a predictive model to classify ALL subtypes.
3. Saving time and increasing reproducibility with predefined analysis templates
4. Using Log points to save results with visuals

Register here to install Qlucore

QOE 3.5:

New plots: Talus and Scree for estimation of data dimensions

Projection score: now with automatic variance filtering tuning to provide optimally selected PCA plot visualization

Tukey statistics available (in a Box plot, and for a variable list export)

More options in 2D plots

Qlucore tools enable researchers to quickly visualize, analyze and perform biological exploration (e.g. GSEA) on various data including RNAseq, microarrays, proteomics, miRNA, methylated DNA, metabolomics, lipidomics, mulitplex and FACS data, clinical data, biomarkers, etc.

Case studies