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
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 a 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
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.
It is possible to run Blast only on the differential expressed genes and not on all the data with OmicsBox. One has to select only those sequences that have differential expressed genes in the OmicsBox project.First, make sure that the name of the sequences in the project match the ones from the differential expression results.
Release OmicsBox version 1.2 (24th of October, 2019) We are happy to announce the following updates for the genome analysis module. New feature includes a new DNA-Seq de novo assembly strategy based on SPAdes.More details can be found below as well as in the online user manual and Genome Analysis Module website. DNA-Seq de Novo Assembly: SPAdes SPAdes (St Petersburg genome
Release OmicsBox version 1.2 (24th of October, 2019) We are happy to announce the following updates for the transcriptomics module. New features include Completeness Assessment and Predict Coding Regions. More details can be found below as well as in the online user manual and Transcriptomics Module website. Completeness Assessment The Completeness Assessment functionality provides quantitative measures for the assessment of transcriptome assembly completeness, based on
Release OmicsBox version 1.2 (24th of October, 2019) We are happy to announce the following updates for the metagenomics module. New feature include OTU Differential Abundance Testing and several new taxonomy plots: Chao1 Diversity, Rarefaction Curves and PCoA. More details can be found below as well as in the online user manual and Metagenomics Module website. New Taxonomy Statistics and Plots
In this analysis, we will reproduce the study that was carried out by Michaela M. Martis et al. in 2017 (doi: http://doi.org/10.1371/journal.pone.0185182) with OmicsBox. Introduction Ascaridia galli is an intestinal parasite which infects a wide range of domestic birds. It is especially important in European farms, where it parasites laying hens and cause some economic problems. The only available treatments are
In this use case we will use the metagenomics tools included in OmicsBox to analyze the microbial communities of two different soda lakes from Brazil. The original study was carried out by Ana P. D. Andreote, et al., 2018 (doi: 10.3389/fmicb.2018.00244). Introduction Soda lakes are special ecosystems found across Africa, Europe, Asia, etc. These lakes show high levels of sodium
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