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DESeq2 is a software package in the field of bioinformatics and computational biology for the statistical programming language R.It is primarily employed for the analysis of high-throughput RNA sequencing (RNA-seq) data to identify differentially expressed genes between different experimental conditions.
PathwaySeq [154] Pathway analysis for RNA-Seq data using a score-based approach. petal Co-expression network modelling in R. ToPASeq: [155] an R package for topology-based pathway analysis of microarray and RNA-Seq data. RNA-Enrich A cut-off free functional enrichment testing method for RNA-seq with improved detection power.
RNA-Seq (named as an abbreviation of RNA sequencing) is a technique that uses next-generation sequencing to reveal the presence and quantity of RNA molecules in a biological sample, providing a snapshot of gene expression in the sample, also known as transcriptome.
The browser allows users to visualize and browse large (up to hundreds of millions of short reads) next generation sequence assemblies. It supports SAM, [20] BAM (the binary version of SAM), and ACE formats. Before browsing assembly data in UGENE, an input file is converted to a UGENE database file automatically. This approach has its pros and ...
Wilbanks and colleagues [3] is a survey of the ChIP-seq peak callers, and Bailey et al. [4] is a description of practical guidelines for peak calling in ChIP-seq data. Peak calling may be conducted on transcriptome/exome as well to RNA epigenome sequencing data from MeRIPseq [ 5 ] or m6Aseq [ 6 ] for detection of post-transcriptional RNA ...
Illumina sequencing: it offers a good method for small RNA sequencing and it is the most widely used approach. [7] After the library preparation and amplification steps, the sequencing (based on the use of reversible dye-terminators ) can be performed by using different systems, such as Miseq System, Miseq Series, NextSeq Series and many others ...
The data produced by single-cell RNA-seq can consist of thousands of cells each with expression levels recorded across thousands of genes. [7] In order to efficiently process data with such high dimensionality many trajectory inference algorithms employ a dimensionality reduction procedure such as principal component analysis (PCA), independent component analysis (ICA), or t-SNE as their first ...
In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. It can be performed on the entire genome, transcriptome or proteome of an organism, and can also involve only selected segments or regions ...
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