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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 ...
When the protein is a transcription factor, the enriched area is its transcription factor binding site (TFBS). Popular software programs include MACS. [ 2 ] 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.
As with any scientific experiment, it is prudent to conduct RNA-Seq in a well controlled setting. If this is not possible or the study is a meta-analysis, another solution is to detect technical artifacts by inferring latent variables (typically principal component analysis or factor analysis) and subsequently correcting for these variables. [58]
The human genome contains on the order of 20,000 genes which work in concert to produce roughly 1,000,000 distinct proteins. This is due to alternative splicing, and also because cells make important changes to proteins through posttranslational modification after they first construct them, so a given gene serves as the basis for many possible versions of a particular protein.
One analysis method, known as gene set enrichment analysis, identifies coregulated gene networks rather than individual genes that are up- or down-regulated in different cell populations. [1] Although microarray studies can reveal the relative amounts of different mRNAs in the cell, levels of mRNA are not directly proportional to the expression ...
ABSSeq a new RNA-Seq analysis method based on modelling absolute expression differences. ALDEx2 is a tool for comparative analysis of high-throughput sequencing data. ALDEx2 uses compositional data analysis and can be applied to RNAseq, 16S rRNA gene sequencing, metagenomic sequencing, and selective growth experiments.
The ChIA-PET method combines ChIP-based methods, [2] and Chromosome conformation capture (3C) based methods, [3] to extend the capabilities of both approaches. ChIP-Sequencing (ChIP-Seq) is a popular method used to identify transciption factor binding sites (TFBS) while 3C has been used to identify long-range chromatin interactions.
SMiLE-seq workflow. SMiLE-seq uses a microfluidic device into which transcription factors, which have been transcribed and translated in vitro, are loaded.Transcription factor samples (~0.3 ng) are modified by the addition of an enhanced green fluorescent protein (eGFP) tag and combined with both target double-stranded DNA molecules (~8 pmol) tagged with Cyanine Dye5 (Cy5) and a double ...