The Multilocus Sequence Typing Analysis Tool of OmicsBox (MLST) is a nucleotide sequence-based approach of characterizing isolates of bacterial species using the sequences of internal fragments of seven housekeeping genes. This video shows step-by-step how to analyze bacterial sequences with the MLST App in OmicsBox. As input, users can provide either DNA-Seq reads in FASTQ or contigs/scaffolds in FASTA format.
This 5-minute video provides a brief introduction to OmicsBox. All main features of all modules are introduced. OmicsBox is a bioinformatics Solution to easy your Omcis Data Analysis. Our workflows get you from raw reads tp insights fast and easy. The presented modules include Transcriptomics, Functional Annotation and Analysis with Blast2GO, the Genome Analysis Module as well as the Metagenomics
RNA-seq data is sometimes difficult to match with proteins, due to the short length of the reads. When this is the case, it might be useful to try to find EST hits, which can then be used to find new protein matches. In this demo, we will show how to retrieve top EST hits and the different options that this tool
OmicsBox/Blast2GO provides an interface to create, edit and run workflows based on the Common Workflow Language (CWL) specification. This interface allows to describe all analysis steps using the functions and tools offered by Blast2GO and connect them to perform a complete analysis in a single run. This video shows step-by-step how to create a workflow from scratch, define the input
The Transcript-level Quantification feature of OmicsBox/Blast2GO allows quantifying the gene and isoform expression of RNA-seq datasets. This video shows step-by-step how to create a count table of aligned sequencing reads and explains in detail the different concepts of expression quantification at transcript level. The application is based on the RSEM software package, which assigns reads to the isoforms they came
The “Create Count Table” feature of OmicsBox/Blast2GO allows quantifying the gene expression of RNA-seq datasets. This video shows step-by-step how to create a count table of raw reads and explains in detail different concepts of expression quantification. The available parameters are inspired by the popular HTSeq Python Package (reference below).
This video shows how to use the ‘Coding-Potential Assessment Tool‘ which allows distinguishing the coding transcripts from the non-coding transcripts. This can be achieved using prebuilt models or building a species-specific model from the NCBI database. The results of the coding potential can be cross-checked with the Blast results and may allow discovering some novel mRNA.
This video shows how to use the ‘Create NCBI GenBank Genome Submission Files’ tool which allows to generate all files (e.g. the Asn1 (.sqn) file) necessary to submit your annotated sequences to the NCBI database. It allows to combine genomic sequences and functional annotations and creates valid GenBank submission files. Additionally, this video explains how to obtain source files (.gff and .annot files), provides
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