• Manuals

Browse the manual

• Introduction
  • The concept of Biomedical Genomics Analysis
  • System requirements
  • Contact information
• QIAseq Panel Analysis
  • Data management
  • The Analyze QIAseq Panels guide
    • Import your reads
    • Start a QIAseq panel analysis
    • Upload to QCI Interpret
  • How to create a custom panel analysis workflow
    • Import QIAGEN Primers
  • Create a custom Trim adapter list (optional)
• Targeted DNA
  • The Identify QIAseq DNA Variants ready-to-use workflows
    • Output from the Identify QIAseq DNA Variants workflow
    • Quality Control for the Identify QIAseq DNA Variants workflow
  • The Identify TMB Status ready-to-use workflows
    • Output from the Identify TMB Status workflow
  • The Detect QIAseq MSI Status (beta) ready-to-use workflow
    • Output of the Detect QIAseq MSI Status workflow
  • Targeted DNA tools detailed description
    • Calculate TMB Score
    • Detect MSI Status (beta)
    • Generate MSI Baseline (beta)
    • Remove and Annotate with Unique Molecular Index
    • Calculate Unique Molecular Index Groups
    • Create UMI Reads
    • Remove Ligation Artifacts
    • Trim Primers of Mapped Reads
    • Annotate Variants with Unique Molecular Index Info
    • Prepare Guidance Variant Track
    • Import Gene-Pseudogene Table
• Targeted RNAscan
  • The Detect QIAseq RNAscan Fusions ready-to-use workflow
    • Output from the Detect QIAseq RNAscan Fusions workflow
    • Interpretation of the Detect QIAseq RNAscan Fusions results
  • Targeted RNAscan tools detailed description
    • Detect Fusion Genes
    • Refine Fusion Genes
    • Annotate Fusions with Known Fusion Information
    • QC for RNAscan Panels
    • Import Known Fusion Information Track
• Targeted RNA
  • The Quantify QIAseq RNA Expression ready-to-use workflow
    • Output from the Quantify QIAseq RNA Expression workflow
  • Targeted RNA tools detailed description
    • The Quantify QIAseq RNA tool
• UPX 3'
  • Demultiplex QIAseq UPX 3' reads
  • The Quantify QIAseq UPX 3' ready-to-use workflow
    • Output from the Quantify QIAseq UPX 3' workflow
• Targeted Methyl
  • The Detect QIAseq Methylation ready-to-use workflow
    • Output from the Detect QIAseq Methylation workflow
    • Finding differentially methylated regions
• QCI Interpret Integration
  • Configuration of the Upload to QCI Interpret tool
  • The Upload to QCI Interpret tool
• QIAseq miRNA Analysis
  • QIAseq miRNA Quantification
    • QIAseq miRNA Quantification outputs
  • QIAseq miRNA Differential Expression
  • QIAseq miRNA Expert Tools
    • Create UMI Reads for miRNA
    • Quantify miRNA
    • Annotate with RNAcentral Accession Numbers
    • Create Combined miRNA Report
• QIAGEN GeneRead DNA Panel Analysis
  • The QIAGEN GeneRead Panel Analysis workflow
    • Output from the QIAGEN GeneRead Panel Analysis
  • Trim Primers and their Dimers of Mapped Reads
• Ready-to-use workflows descriptions and guidelines
  • General Workflow
  • Somatic Cancer
  • Hereditary Disease
• Getting started
  • Import sequencing data
  • Prepare Raw Data
• Whole genome sequencing (WGS)
  • General Workflows (WGS)
    • Annotate Variants (WGS)
    • Identify Known Variants in One Sample (WGS)
  • Somatic Cancer (WGS)
    • Filter Somatic Variants (WGS)
    • Identify Somatic Variants from Tumor Normal Pair (WGS)
    • Identify Variants (WGS)
  • Hereditary Disease (WGS)
    • Filter Causal Variants (WGS-HD)
    • Identify Causal Inherited Variants in Family of Four (WGS)
    • Identify Causal Inherited Variants in Trio (WGS)
    • Identify Rare Disease Causing Mutations in Family of Four (WGS)
    • Identify Rare Disease Causing Mutations in Trio (WGS)
    • Identify Variants (WGS-HD)
• Whole exome sequencing (WES)
  • General Workflows (WES)
    • Annotate Variants (WES)
    • Identify Known Variants in One Sample (WES)
  • Somatic Cancer (WES)
    • Filter Somatic Variants (WES)
    • Identify Somatic Variants from Tumor Normal Pair (WES)
    • Identify Variants (WES)
    • Identify and Annotate Variants (WES)
  • Hereditary Disease (WES)
    • Filter Causal Variants (WES-HD)
    • Identify Causal Inherited Variants in Family of Four (WES)
    • Identify Causal Inherited Variants in Trio (WES)
    • Identify Rare Disease Causing Mutations in Family of Four (WES)
    • Identify Rare Disease Causing Mutations in Trio (WES)
    • Identify Variants (WES-HD)
    • Identify and Annotate Variants (WES-HD)
• Targeted amplicon sequencing (TAS)
  • General Workflows (TAS)
    • Annotate Variants (TAS)
    • Identify Known Variants in One Sample (TAS)
  • Somatic Cancer (TAS)
    • Filter Somatic Variants (TAS)
    • Identify Somatic Variants from Tumor Normal Pair (TAS)
    • Identify Variants (TAS)
    • Identify and Annotate Variants (TAS)
  • Hereditary Disease (TAS)
    • Filter Causal Variants (TAS-HD)
    • Identify Causal Inherited Variants in Family of Four (TAS)
    • Identify Causal Inherited Variants in Trio (TAS)
    • Identify Rare Disease Causing Mutations in Family of Four (TAS)
    • Identify Rare Disease Causing Mutations in Trio (TAS)
    • Identify Variants (TAS-HD)
    • Identify and Annotate Variants (TAS-HD)
• Whole Transcriptome Sequencing (WTS)
  • Annotate Variants (WTS)
  • Compare Variants in DNA and RNA
  • Identify Candidate Variants and Genes from Tumor Normal Pair
  • Identify Variants and Add Expression Values
  • Identify and Annotate Differentially Expressed Genes and Pathways
• Batching workflows
• Appendices
  • Legacy tools
    • Trim Primers of Mapped Single Reads
    • Trim Primers of Mapped Paired End Reads
  • Install and uninstall plugins
    • Install
    • Uninstall
• Bibliography

QIAseq miRNA Differential Expression

The workflow calculates differential expressions for expression tables with associated metadata using multi-factorial statistics based on a negative binomial Generalized Linear Model (GLM). Both Grouped on Mature and Grouped on Seed expression tables can be used.

The expression tables are sent to:

• Create Heat Map for miRNA The tool creates a two dimensional heat map of expression values. Each column corresponds to one sample, and each row corresponds to a feature (a miRNA or seed sequence). The samples and features are both hierarchically clustered.

• Differential Expression for miRNA The tool performs a statistical differential expression test and outputs Statistical Comparison Tables that are used as input for the following tools:
  • Gene Set Test Note that this will not yield any results when the workflow is run with Seeds, as no Gene Ontology annotations are known for seeds.

  • Create Expression Browser This creates a table where each row includes the expression values of all samples and the contents of all the statistical comparison tables.

  • Create Venn Diagram for RNA-Seq The Venn diagram comparison visualizes the overlap between the differentially expressed miRNAs in the selected statistical comparison tables. The miRNA considered to be differentially expressed can be controlled by setting appropriate p-value and fold change thresholds.

To run the workflow, go to:

Ready-to-Use Workflows | Small RNA Sequencing () | QIAseq miRNA Differential Expression ()

Choose the expression data to be analyzed (figure 9.9). The workflow takes Grouped on mature, Grouped on custom database and Grouped on seed expression tables, but note that only samples generated using the same parameters should be analyzed together.

Figure 9.9: Select the expression data to be compared.

Then select the QIAseq Small RNA Reference Data Set as in figure 9.10. You can download the Data Set if you have not done so before.

Figure 9.10: Select and download if necessary the relevant Reference Data Set.

Following this, the parameters for the QIAseq miRNA Differential Expression need to be specified (figure 9.11).

Figure 9.11: Selecting parameters for QIAseq miRNA Differential Expression.

Metadata table Select a metadata object that associates the selected input objects to metadata used by the RNA-Seq analysis.

Test differential expression due to Select the factor to be tested for differential expression.

Comparisons Select groups to be compared. It is possible to choose between "Across groups", "All group pairs", and "Against control group".

Control group If "Against control group" was selected in "Comparisons", a control group must be selected.

An example of a metadata table is shown in figure 9.12.

Figure 9.12: Select the expression data to be compared.

In the final step, standard result handling is performed: the selected parameters can be previewed, and an output location must be chosen.

The workflow will output the following files:

• a Gene Set Test table, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Gene_Set_Test.html.

• a Venn diagram, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Create_Venn_Diagram_RNA_Seq.html.

• a Statistical comparison table, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Statistical_comparison_tracks.html. This table can be uploaded to Ingenuity Pathway Analysis.

• an Expression browser, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Create_Expression_Browser.html.

• a Heat Map, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Create_Heat_Map_RNA_Seq.html.

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