RNA-seq/transcriptomics workflows - User Guide to SeqMan NGen - 18.0

The following table describes each of the workflows available in the RNA-seq/transcriptomics tab of the Workflow screen.

Group	Workflow	Description
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 a variety of ways: Use SeqMan Pro’s 3-tabbed Feature Table for downstream analysis. Each tab (All Features, Gene Features, CDS Features) displays expression values in a column entitled “RPKM”. If the sample is part of a replicate set, a second column entitled “RPKM – Replicate” displays the expression value for the feature determined from the replicate set. Display a Sashimi plot for the assembly in GenVision Pro. Sashimi plots are designed to display data indicative of mRNA splicing, and are generated automatically during RNA-Seq assembly. See RNA-Seq reference-guided workflow output for a list of output files resulting from this type of assembly. Use ArrayStar’s Gene and Isoform tables to filter for differentially-expressed genes of interest. ArrayStar tables can also display any DESeq2 or edgeR statistics included in the assembly. Access editable Bioconductor volcano and PCA plots from the output folder. These are available only if you used DESeq2 as the normalization method.
	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 Assembly	De novo miRNA	De novo assemble novel miRNAs.

Create an assembly for phased variant analysis

Include DESeq2 or edgeR statistics

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