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The differential expression (DE) analysis has been used in bulk RNA-seq analysis for many years. It allows us to statistically measure changes in gene expression levels between different groups. With bulk RNA-seq analysis many cells are sequenced at the same time, so gene expression levels are commonly measured at the tissue level. Thus, the differences between samples and conditions are

Transcriptome sequencing (RNA-Seq) produces big amounts of valuable information on all transcribed elements in the genome. With RNA-Seq, researchers can interrogate the transcriptome to profile gene expression, uncover alternative splicing, and identify novel and discard aberrant transcripts and coding variants, among others. The resulting BAM Files are the source of information for all proceeding step

Specific tools for a new generation of sequencing Third Generation Sequencing (TGS) is getting a notable increase in relevance by surpassing some of the limitations of NGS technologies. In that sense, the main feature of TGS is the capacity to produce much longer reads than NGS. These long reads facilitate the assembly of complex genomes and the study of alternative

Transcriptome analysis is a challenging bioinformatic problem. In eukaryotic transcriptomes, alternative splicing and alternative polyadenylation are the most complex issues. Genome-wide analysis of alternative splicing has been studied with short-read RNA sequencing for a while. Nevertheless, this technology needs a subsequent assembly, which is difficult to be resolved in ambiguities in complex loci.