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By incorporating the negative binomial distribution, DESeq2 accurately models the dispersion of gene expression counts and provides more reliable estimates of differential expression. DESeq2 also offers an adaptive shrinkage procedure, known as the "apeglm" method, which is particularly useful when dealing with small sample sizes. [ 6 ]
Using DESeq2 as a framework, DEvis provides a wide variety of tools for data manipulation, visualization, and project management. DEXSeq is Bioconductor package that finds differential differential exon usage based on RNA-Seq exon counts between samples. DEXSeq employs negative binomial distribution, provides options to visualization and ...
Within computational biology, an MA plot is an application of a Bland–Altman plot for visual representation of genomic data. The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values.
Methods: Most tools use regression or non-parametric statistics to identify differentially expressed genes, and are either based on read counts mapped to a reference genome (DESeq2, limma, edgeR) or based on read counts derived from alignment-free quantification (sleuth, [106] Cuffdiff, [107] Ballgown [108]). [109]
Label-free quantification experiment with 3 samples, 3 LC-MS files and 5 precursor ions/peptides. Intensities at the peak of the chromatographic peaks are used for quantification in this particular case. Peptides are identified via fragmentation mass spectra, and some of the precursor ions will be quantified, but not mapped to any peptide sequence.
In statistics, quantile normalization is a technique for making two distributions identical in statistical properties. To quantile-normalize a test distribution to a reference distribution of the same length, sort the test distribution and sort the reference distribution.
Representative sequences covering 27% of 2000 cohabitation sequences between age 15 and 30 (extract of biographical data from the Swiss Household Panel) In Sequence analysis in social sciences , representative sequences are used to summarize sets of sequences describing for example the family life course or professional career of several ...
Schematic overview of the modular structure underlying procedures for gene set enrichment analysis. Gene set enrichment analysis (GSEA) (also called functional enrichment analysis or pathway enrichment analysis) is a method to identify classes of genes or proteins that are over-represented in a large set of genes or proteins, and may have an association with different phenotypes (e.g ...