The following table describes each of the workflows available in the RNA-seq/transcriptomics tab of the Workflow screen.
|Quantitative analysis||RNA-seq|| RPKM gene expression quantification and differential gene expression using DESEQ2 and EdgeR from BioConductor. First-pass assembly is done using the usual XNG assembler. Second-pass assembly utilizes the QNG analysis module to determine expression level statistics. For each sample in a project, two new files for each contig/chromosome are put into the .assembly package. These contain the QNG calculated expression values for each gene and its isoforms: -[contig number].genes-features and -[contig number].isoforms-features.
To learn how to use the output of an RNA-Seq de novo transcriptome assembly as input for the RNA-Seq reference-guided workflow, see Use RNA-Seq de novo transcriptome output as a reference.
After performing an RNA-Seq reference-guided assembly, you can view the results in any of three applications:
|ChIP-seq||Choose from several different normalization and peak detection methods, including ERANGE and MACS.|
|miRNA||miRNA gene expression quantitation and discovery of new miRNAs.|
|De Novo Assembly||De novo transcriptome||Large capacity assembly of transcriptome sequence data with auto-annotation of assembled transcripts. In the past, de novo assembly of RNA-Seq data could result in thousands of contigs representing the expressed transcripts, without any context or labels. For Lasergene 13.0 and later, SeqMan NGen automatically attempts to group contigs from the same gene, and then name and annotate them based on the best match to a collection of annotated reference sequences. Two different SeqMan NGen assembly engines are used to optimize your results. Note that results from this workflow are non-quantitative. Result files for this workflow are described in detail in RNA-Seq de novo transcriptome workflow output. (Also called the “StarBlast” workflow)|
|De novo miRNA||De novo assemble novel miRNAs.|
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