Most transcripts assembled from eukaryotic and prokaryotic RNA-Seq data are expected to code for proteins. The most practical procedure to identify likely coding transcripts is a sequence homology search, such as by BLASTX, against sequences from well-annotated and related species. Predicting coding regions is crucial to determine the molecular role that transcripts play in the cell. Unfortunately, such well-annotated nearby
De novo transcriptome assemblies are required to analyze RNA-seq data from a species for which there is no reference genome. Once the assembly is complete, researchers need to know how good it is or compare the quality of similar assemblies generated by different parameters. There are several ways to characterize the quality of transcriptome assemblies. A good metric of assembly
DNA sequencing is the process of determining the nucleic acid sequence in DNA, and it is the technology by which the genome of a species can be characterized. Despite the advent of next-generation sequencing, current DNA sequencing technologies cannot read whole genomes at once, but rather reads small pieces of between 20 and 30.000 bases, depending on the technology used.
High-throughput sequencing of RNA has revolutionized the study of species for which a reference genome is not available or incomplete by enabling the large-scale analysis of their transcriptomes. While analyses of model organisms generally rely on a reference genome, studies of non-model organisms usually lack this advantage. In the absence of an appropriate reference genome, de novo transcriptome assembly is
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