High Dimensional Data & Hierarchical Regression

In a high-throughput experiment one performs measurements on thousands of variables (e.g. genes or proteins) across two or more experimental conditions. In bioinformatics, we come across such data generated using technologies like Microarrays, Next generation sequencing, Mass spec etc. Data from these technologies have their own pre-processing, normalising and quality checks (see here and here … Continue reading High Dimensional Data & Hierarchical Regression


Next Generation Sequencing Data Quality Checks

Analysing a variety of Next Generation Sequencing (NGS) data sets from different projects over the past years, we have developed a general workflow to assess data quality. This is a guideline and can be applied at various steps of the analysis, starting with raw FASTQ file checks. FASTQ Quality Checks: Generally the simplest tool to … Continue reading Next Generation Sequencing Data Quality Checks

Compare Transformations & Batch Effects in Omics Data

While analysing high dimensional data, e.g. from Omics (Genomics, Transcriptomics, Proteomics etc.) - we are essentially measuring multiple response variables (i.e. genes, proteins, metabolites etc.) in multiple samples, resulting in a $latex rXn$ matrix X with r variables and n samples. The data capture can lead to multiple batches or groups in the data - … Continue reading Compare Transformations & Batch Effects in Omics Data