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Qlucore Omics Explorer 3.11 introduces new functionality for the flexible import and analysis of proteomics data, Olink® panel data, and qPCR data, together with enhancements in visualization tools. In this webinar, we will demonstrate the import, pre-processing, and normalization of LC-MS proteomics data, the import of Olink® NPX Map data files, and the import and normalization of qPCR data. We will also present the new options for flexible label handling in 2D plots, such as scatter plots, as well as improvements in 3D PCA plot visualization. This session is designed to highlight practical workflows and provide insights into how the latest features can support deeper biological interpretation and more efficient analysis.

Free online hands-on training. Learn how to easily analyze your experiment data yourself. This is an introduction to how you can explore and analyze experimental data using a highly visual and interactive tool in several hands-on exercises. You will do exercises on visualization of data in PCA plots and Heatmaps, run a statistical test to find discriminating variables, and learn how to explore a dataset to find interesting clusters. You do not need any previous experience with the program. No programming is needed. Course material and a training license will be sent out prior to the course.

Qlucore Omics Explorer 3.11 introduces new functionality for the flexible import and analysis of proteomics data, Olink® panel data, and qPCR data, together with enhancements in visualization tools. In this webinar, we will demonstrate the import, pre-processing, and normalization of LC-MS proteomics data, the import of Olink® NPX Map data files, and the import and normalization of qPCR data. We will also present the new options for flexible label handling in 2D plots, such as scatter plots, as well as improvements in 3D PCA plot visualization. This session is designed to highlight practical workflows and provide insights into how the latest features can support deeper biological interpretation and more efficient analysis.

Olink® panels can be used to measure proteins, including biomarkers, and are applied in a wide range of research and clinical contexts. In this webinar, we will guide you through the steps required to begin analyzing Olink data. Qlucore Omics Explorer supports data import from multiple Olink panels. You simply export normalized data from the Olink® software and use the Qlucore Import Wizard to import files—whether organized as a matrix or as vectors (such as NPX Map). From there, it is straightforward to perform the necessary data cleaning and normalizations, preparing your dataset for statistical tests, visualizations, and in-depth analysis.

Many users get RNA-seq data in the form of a raw count matrix, either directly in an excel/csv/ txt file, or through aligned BAM file import. With the program you import the data, select the normalization method you want to apply, and the visualization and statistical tests you want to utilize. In this webinar we will present both the VST normalization and the use of DESeq2 statistical tests (Wald and LRT), as well as TMM/TPM/FPKM normalization and standard statistics (t-test/ANOVA etc).

Proteomics data—for example from LC-MS—is often provided as CSV or TXT files generated by an instrument software. In this webinar, we demonstrate how to use the Qlucore Import Wizard, which supports both unnormalized and normalized data. You can pre-process your dataset by handling empty cells, applying prefiltering, performing transformations such as offsetting data or applying thresholds and applying Quantile Normalization. Once the data is prepared, you can take advantage of the inbuilt statistical tests and visualization tools in Qlucore Omics Explorer to analyze and explore your proteomics data with confidence.

qPCR data is often provided as CSV or TXT files, and it can be imported directly using the Qlucore Import Wizard. In this webinar, we will demonstrate how you can import and pre-process your data, manage empty cells, apply prefiltering, perform log transformations, and carry out householding based Normalization. You can also choose to remove household variables and add additional annotations to enrich your dataset. Once prepared, you can utilize the inbuilt statistical tests and visualization tools in Qlucore Omics Explorer to support your analysis and exploration work.

Free online hands-on training. Learn how to easily analyze your experiment data yourself. This is an introduction to how you can explore and analyze experimental data using a highly visual and interactive tool in several hands-on exercises. You will do exercises on visualization of data in PCA plots and Heatmaps, run a statistical test to find discriminating variables, and learn how to explore a dataset to find interesting clusters. You do not need any previous experience with the program. No programming is needed. Course material and a training license will be sent out prior to the course.