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
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 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 from
The “Create Count Table” feature of 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
The Time Course Expression Analysis tool allows performing a differential expression analysis of expression data arising from a time course RNA-seq experiment. This application is based on the maSigPro Bioconductor package, which implements a two-step regression strategy to detect genes with significant temporal expression changes and significant differences between experimental groups. This video shows the analysis of count data coming
The Pairwise Differential Expression Analysis tool is designed to perform differential expression analysis of count data arising from an RNA-seq experiment. The application, which is based on the software package “edgeR”, allows the identification of differentially expressed genes between two experimental conditions by applying quantitative statistical methods. This video shows the performance of a pairwise differential expression analysis in which
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