TCC - TCC: Differential expression analysis for tag count data with robust normalization strategies
This package provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in depended packages.
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immunooncologysequencingdifferentialexpressionrnaseq
5.67 score 47 scripts 747 downloadsCircSeqAlignTk - End-to-End Analysis of Small RNA-Seq Data from Viroids
CircSeqAlignTk is a toolkit for the analysis of RNA-Seq data derived from circular genome sequences, with a primary focus on viroids, circular RNAs typically consisting of a few hundred nucleotides. The toolkit supports an end-to-end analysis pipeline, from alignment to visualization.
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sequencingsmallrnaalignmentsoftware
4.00 score 4 scripts 350 downloads