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• Introduction
• General Description
  • Supported sample kits and sequencing platforms
  • Accessing RNA-seq Analysis Portal
  • Analysis credits for RNA-seq Analysis Portal
• Getting Started
  • Upload sequencing data
  • Align and count
  • Create experiment
  • View and filter results
  • What's next - send results downstream
  • Design follow-up experiments in GeneGlobe
• User Interface
  • Analysis Portal page
    • Front page and Projects overview
    • Project view
    • Send copy of project
  • Samples page
• Starting Analyses
  • Align and count dialog
    • QIAseq UPX 3' Transcriptome Kit and QIAseq UPXome RNA Lib Kit specific settings
  • Create experiment dialog
    • Sample grouping
    • Experimental design
  • Compare analyses dialog
• Viewing Results
  • Experiment summary and QC report
  • Differential expression view
    • Feature table
    • Volcano plot
    • Heat map
    • Biological insights table
    • Filter
    • Send results to GeneGlobe
    • Send results to QIAGEN IPA
  • Comparison view
• RNA-seq Analysis Portal analysis explained
  • Align and count analysis workflows
    • Align and count - QIAseq miRNA Library Kit
    • Align and count - QIAseq UPX 3' Transcriptome Kit
    • Align and count - QIAseq UPXome RNA Lib Kit
    • Align and count - Demultiplexed RNA sample kits
  • Create experiment analysis workflow
  • Taxonomic profiling of unmapped reads
  • Compare analyses
• Appendix A - Sequence file naming pattern
• Appendix B - Reference and annotation information
  • General references and annotations
  • Sample kit specific resources
• Appendix C - Analysis workflow versions, species support and parameters
  • QIAseq miRNA Library Kit (Illumina)
  • QIAseq miRNA Library Kit (Thermo Fisher)
  • QIAseq UPX 3' Transcriptome Kit
  • QIAseq UPXome RNA Lib Kit
  • QIAseq UPXome RNA Lib Kit (N6-T RT primer)
  • QIAseq UPXome RNA Lib Kit (ODT-T RT primer)
  • QIAseq UPXome RNA Lib Kit (N6-T + ODT-T RT primers)
  • QIAseq FastSelect RNA Lib Kit (N6-T RT primer)
  • QIAseq FastSelect RNA Lib Kit (ODT-T RT primer)
  • QIAseq FastSelect RNA Lib Kit (N6-T + ODT-T RT primers)
  • QIAseq Stranded mRNA Select/Stranded Total RNA Lib Kit
  • TruSeq Stranded Total RNA Library Prep (Human/Rat, Gold, Globin)
  • Illumina Stranded Total RNA Prep with Ribo-Zero Plus
  • NEBNext Ultra II Directional RNA Library Prep Kit for Illumina
  • KAPA RNA HyperPrep Kit
  • SMARTer Stranded Total RNA Sample Prep Kit - HI Mammalian/Low Input Mammalian
  • Collibri Stranded RNA Library Prep Kit for Illumina Systems
• Appendix D - RNA-seq Analysis Portal for QIAGEN IPA users
• Appendix E - Quality control details
  • QIAseq miRNA Library Kits
  • QIAseq UPX 3' Transcriptome Kits
  • QIAseq Stranded RNA Library Kits (FastSelect RNA Library Kit, Stranded mRNA/Stranded Total RNA Library Kits), QIAseq UPXome Kit, and all third-party kits

Create experiment analysis workflow

The differential expression analysis report summarizes the analysis results from the following tools. Specific parameters for the individual sample kits are listed in Appendix C.

• Differential Expression for RNA-Seq. Performs a differential expression test using multi-factorial statistics based on a negative binomial GLM. The tool supports paired designs and can control for batch effects.
• Create Heat Map for RNA-Seq. Samples and features are hierarchically clustered to create a two dimensional heat map of expression values. Each column contains data for a particular sample, and each row contains data for a particular feature.
  The following filtering and normalization is carried out when producing the heat map:
  • Log CPM (Counts per Million) values are calculated for each feature. The CPM calculation uses the effective library sizes as calculated by the TMM normalization.
  • A Z-score normalization is performed across samples for each gene: the counts for each gene are mean centered, and scaled to unit variance.
  • Genes or miRNAs with zero expression across all samples or invalid values (NaN or +/-Infinity) are removed.

The tools are described in more detail in the QIAGEN CLC Genomics Workbench manual:

• https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/2103/index.php?manual=Differential_Expression_RNA_Seq.html
• https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/2103/index.php?manual=Create_Heat_Map_RNA_Seq.html

IPA submission and analysis. Prior to being passed on to IPA, the list of features is marked to indicate which to consider for the IPA analysis. The approach is as follows:

1. Select features with an FDR p-value <0.05. If this leaves more than 1000 features, then:
2. Select the 1000 features with the largest absolute fold change, keeping the ratio of up- and down-regulated features.

The uploaded features are used as input for an IPA Core Analysis.

Identification of qPCR normalization genes. The following filtering and selection is applied to identify stably expressed genes that can be used for normalization is e.g. qPCR assays.

1. Filter features:
   • Absolute fold change <1.03
   • FDR p-value >0.05
   • Minimum CPM (Counts per Million, TMM-adjusted) for each group >25
2. Select the 20 features with smallest absolute fold change

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