Transcriptomics analysis in R

R is an open-source statistical programming language that used to manipulate data, to perform statistical analysis,and to present graphical and other results. R consists of a core language, additional 'packages' distributed with the R language, and a very limited number of packages contributed by the broader community .

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Many authors contribute to R, so there can be a frustrating inconsistency of documentation and interface.

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A matrix is also a rectangular data structure, but subject to the constraint that all elements are the same type. A matrix is created by taking a vector, and specifying the number of rows or columns the vector is to represent.

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A package is installed only once per R installation, but needs to be loaded (with library) in each session in which it is used.

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The biostrings package provides tools for working with sequences.

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Alignment of RNA is very important to get a reference from genome or transcriptome.

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Main adjustment for sequencing depth and compositional bias called as specialty applications.

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Identification of Diferentially Expressed Genes (DEGs) is identification of expressed genes possible for unsignificant differences and weakly expressed ones.

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Enrichment analysis of functional annotations is gene ontology analysis of obtained gene sets from steps specialty applications and cluster analysis.

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Ambiguous mappings should not be removed, because there is evidence for their origin.

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