> For the complete documentation index, see [llms.txt](https://knowledge.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://knowledge.illumina.com/software/dragen/software-dragen-faq-list/000010218.md).
# DRAGEN Analysis Pipelines FAQ for Illumina Rapid RNA Kits
**How are stranded vs non**-**stranded RNA libraries differentiated in DRAGEN RNA setup?**
For Rapid RNA, the default setting of A-Auto-Detect is correct, so no other settings are required.
In the Advanced Settings options for RNA-seq library type ([source](https://basespace.illumina.com/apps/18414396/start-internal?)):
* **A** - Auto-Detect, the default. For this value, DRAGEN examines the first reads/pairs in the dataset to automatically determine the correct library type.
* **IU** - Paired-end unstranded library.
* **ISR** - Paired-end stranded library in which read2 matches the transcript strand (eg, TruSeq RNA).
* **ISF** - Paired-end stranded library in which read1 matches the transcript strand.
* **U** - Single-end unstranded library.
* **SR** - Single-end stranded library in which reads are in reverse orientation to the transcript strand (eg, TruSeq RNA).
* **SF** - Single-end stranded library in which reads match the transcript strand.
**For Rapid RNA Enrichment analysis, what are the differences between DRAGEN Enrichment App output versus DRAGEN RNA with Enrichment options?**
* DRAGEN RNA App v 4.4 does not include Enrichment analysis, but this is planned for future version 4.7 (planned for release in Q2 2027). Currently users must run the DRAGEN Enrichment App to see Picard metrics.
* DRAGEN Enrichment App: the DRAGEN Enrichment v4.3.13 Summary provides a Picard metrics csv file. The newer DRAGEN enrichment version (4.4 or 4.5) does not have the same Picard metrics option. There is a new presentation of similar metrics in the DRAGEN Enrichment Report.
* The DRAGEN Enrichment App automatically removes duplicate reads, which may result in the Padded Read Enrichment (PRE) to be low for small panels with high duplicate rates. PRE is defined by the BED files. 150 bp is the standard padding for PRE definition. Therefore, with the 150 bp padding, this includes any reads mapping to the genome over intron/exon boundaries. DRAGEN Enrichment uses the DNA mapper and has no knowledge of gene structure. Hence, reads covering intron exon boundaries are included in the PRE calculation.
**What is the difference between the % Stranded and % Exonic Stranded reads metrics in the DRAGEN RNA report?**
When analyzing Rapid RNA prep data with the non-stranded workflow, the DRAGEN RNA v4.4 shows 95% Stranded, but 48% Exonic Stranded data from mRNA. Future versions of DRAGEN RNA App reports will only show Exonic Stranded metrics.
In v 4.4, mousing-over the DRAGEN Report Summary tab column headers shows the following definitions:
* **% Stranded**: Percentage of fragments mapped to a specific reference orientation.
* **% Exonic Stranded**: Percentage of stranded fragments mapped to the correct orientation of an exon.
**Can DRAGEN RNA perform single nucleotide variant (SNV) calling?**
Yes, but SNV calling is off by default. It must be selected as an option in the App setup.
**In the DRAGEN RNA Report Summary Tab, how is % Abundant defined?**
Abundant RNA includes Ribosomal (rRNA) and mitochondrial RNA. Mousing-over the column header shows "% of non-informative reads".
**In the DRAGEN RNA Report Gene Coverage Tab, how are fragment alignments defined?**
DRAGEN RNA App help page for Gene Expression defines different fragment types, [here](https://help.dragen.illumina.com/dragen-v4.4/product-guide/dragen-v4.4/dragen-rna-pipeline/gene-expression-quantification).
**How does the analysis differentiate between protein coding regions and UTRs?**
These are both included in Transcript alignments. There is no separate annotation of UTRs versus coding sequence alignments in DRAGEN v4.5. UTRs are part of the Transcripts, but they are not protein coding regions of the transcripts. UTRs are considered part of the Exons. Older versions of the RNA-Seq Alignment App reported UTR alignment separately from Coding regions.
**In the DRAGEN RNA Report Gene Coverage Tab, how are Unknown transcript fragments alignments defined?**
These are defined as read pairs that partially align with an exon but overlap non-exonic regions which could be derived from pre-spliced transcripts or novel alternative splicing isoforms. These most often represent reads overlapping intron/exon boundaries in pre-spliced transcripts which are observed in Total RNA and RNA enrichment preps. The threshold for a read to be considered Unknown if it overlaps and intron/exon boundary is a 3 bp or more not matching the transcript exons.
**How does DRAGEN RNA handle assignment of reads aligned to overlapping transcripts for Gene Expression for Gene counts and Transcript counts?**
Alignment of reads to overlapping annotated genes are partially weighted to both genes in the counting application of Salmon used by DRAGEN RNA App. See the Salmon publication in the "What is the underlying algorithm for DRAGEN RNA?" question below for more details on Salmon. Non-annotated genes that are not present in the GTF files will not be assigned any read counts.
**In thee DRAGEN RNA Report, where is the total number of genes or transcripts detected?**
DRAGEN RNA reports the number of genes present at 1x, 10x and 100x median coverage depth. This includes both protein coding and non-coding genes.
Users may be seeking a metric that reports the Total # of Genes and Total # of transcripts detected above a minimum threshold, such as 5 reads. This is not currently reported in the DRAGEN RNA Report. This can be generated from the Quant.sf files for each sample and which is used in downsampling the reads to determine gene and transcript sensitivity. The Quant.sf is aligned to Transcripts, but there are multiple transcripts annotated per gene, so the Gene.quant.sf can also be used for gene-level quantification across all transcript versions.
**How are duplicate reads identified in DRAGEN RNA and are duplicates used for fusions, splice variants, and SNV calling?**
Duplicate Marking
DRAGEN RNA can detect duplicate reads, which are defined as fragments that have both ends mapping to the same (clipping-adjusted) position during alignment. In RNA-seq data, the reads can represent PCR duplicates during library prep or as a result of deep coverage of highly expressed regions.
If `--enable-duplicate-marking` is set to `true` (note that for BaseSpace DRAGEN RNA app launch, duplicate marking is on by default), duplicate fragments are marked in the BAM file and the total number of duplicate reads is reported as a mapping metric. Marking of duplicates does not affect gene expression quantification. Duplicate marking is required to be on for gene fusion calling and is strongly recommended for splice variant calling. See the page [here](https://help.dragen.illumina.com/dragen-v4.4/product-guide/dragen-v4.4/dragen-rna-pipeline/rna-alignment) for more information.
Padded Unique read enrichment may be the same, but duplicates increase with lower library preparation input. Therefore, when duplicates are removed to assess unique reads, there is more taken away from low input samples, so coverage will drop.
RNA Enrichment
DRAGEN Enrichment App will always remove duplicates by default, resulting in lower mean target coverage of unique reads with lower library preparation input due to higher duplicates. For example, a higher input of 100 ng has fewer duplicates, resulting in higher Mean Target coverage than a lower 10 ng input with higher duplicates.
**How does DRAGEN assign reads to one of multiple gene transcripts, where genes are overlapping?**
The Salmon algorithm assigns weighted partial counting towards each gene where a read maps to multiple genes.
**What is the underlying algorithm for DRAGEN RNA?**
The algorithm is an adaption of the Salmon algorithm. The main difference is the Illumina algorithm works on genome wide alignments the mapper produces; whereas, Salmon uses either pseudoalignments or a transcript aligned bam as input.
See the following for additional information on Salmon.
*
*
Overview
Salmon is a tool for quantifying the expression of transcripts using RNA-seq data. Salmon uses new algorithms (specifically, coupling the concept of *quasi-mapping* with a two-phase inference procedure) to provide accurate expression estimates quickly while using little memory. Salmon performs its inference using an expressive and realistic model of RNA-seq data that takes into account experimental attributes and biases that may be observed in RNA-seq data.
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| *For any feedback or questions regarding this article (Illumina Knowledge Article #10218), contact Illumina Technical Support* [*techsupport@illumina.com*](mailto:techsupport@illumina.com?subject=Question%2FFeedback%20Regarding%20Illumina%20Knowledge%20Article%20#000010218%20-%20Software%20\&body=Dear%20Illumina%20Technical%20Support,%0D%0A%0D%0A)*.* |
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