Tag Archives: Principal Component Analysis

Next-generation sequencing (NGS) techniques have been used to generate various molecular maps including genomes, epigenomes, and transcriptomes. Transcriptomes from a given cell population can be...

Heatmaps are an indispensible visualization tool for examining large-scale snapshots of genomic activity across various types of next-generation sequencing datasets. However, traditional heatmap software do not typically offer multi-scale insight across multiple layers of genomic analysis (e.g., differential expression analysis, ...

RNA-seq analysis is becoming a standard method for global gene expression profiling. However, open and standard pipelines to perform RNA-seq analysis by non-experts remain challenging due to the large size of the raw data files and the hardware requirements for ...

CSBB is a tool that can help people in the bioinformatics and biology community perform custom bioinformatics downstream analysis without writing a single line of code. CSBB is a command line based bioinformatics suite to analyze biological data acquired through ...

Worldwide growth and performance-enhancing substances are used in cattle husbandry to increase productivity. In certain countries however e.g., in the EU, these practices are forbidden to prevent the consumers from potential health risks of substance residues in food. To maximize ...

Dimensionality reduction techniques such as principal component analysis (PCA) are common approaches for dealing with noisy, high-dimensional data. Though these unsupervised techniques can help uncover interesting structure in high-dimensional data they give little insight into the biological and technical considerations ...

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analysing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalisation, ...