Sequence of Indices (Barcodes) Used for Multiplexing

QuantSeq libraries are intended for a high degree of multiplexing. With QuantSeq for Illumina up to 9,216 samples can be uniquely barcoded in one lane by using the up to 96 external i7 indices (7001-7096) included in the kit together with the 96 external i5 indices (5001-5096), which are part of the Lexogen i5 6 nt Dual Indexing Add-on Kit (Cat. No. 047).

pdf Lexogen i7 and i5 Index Sequences – update 05.05.2020

Automated Data Analysis Pipeline

The QuantSeq data analysis pipeline has been implemented on the BlueBee® Genomics Platform and in the Partek Flow software, offering to every user, even without bioinformatics experience, the opportunity to analyze QuantSeq samples in a convenient and fast way.

The pipeline on the BlueBee® Genomics Platform is accessible through a complimentary code provided with each QuantSeq kit. Learn more and get started at For using your activation code register an account with BlueBee ( and upload your data (fastq.gz files).

Activation codes for additional runs can be purchased from Lexogen via the webshop. Reference genomes for new species may be added upon request. However, this will incur an additional fee. Please enquire about the feasibility of upload for your genome of interest, and pricing via

NOTE! Before starting your library prep, please check the online Frequently Asked Questions (FAQ 1.27), or contact to see if your species is available on the BlueBee Platform. Lexogen can add reference genomes for new species to the BlueBee Data Analysis Pipeline upon request. Please note this will incur a fee.
New reference genome implementation timelines are dynamic due to feasibility checks and formatting adjustments and therefore cannot be precisely guaranteed. We recommend submitting your request as early as possible prior to sequencing your libraries. New genome upload acceptance is also subject to change in the case of compatibility issues. For all related enquiries, please contact

The QuantSeq pipeline in the Partek Flow software is available for any Partek Flow user at

The QuantSeq pipeline is available on the OnRamp Platform ROSALIND, which allows Lexogen’s customers to analyze, interpret and collaborate globally on differential gene expression analysis without the need for specialized bioinformatics or programming skills. Every Lexogen’s customer purchasing a QuantSeq kit (FWD or REV) before July 1, 2021 is eligible for 24 free runs on ROSALIND. Contact to activate your free runs. For additional runs, please contact your local sales representative and

QuantSeq – FWD Data Analysis

The following analysis pipeline demonstrates a principal workflow.
The used tools are freely available and to a great extend part of the Galaxy platform1. All proprietary Software, for instance CLC workbench, should perform similarly.
The script examples uses mainly the bash internal for-loop; in Galaxy for instance, the single files have to be processed manually one by one.
Following software packages (and their dependencies) should be installed when following the given protocol:

  • Samtools
  • FastQC
  • bbmap
  • STAR aligner

Create a working directory and the subdirs fastq, qualitycheck and download the de-multiplexed fastq files into the fastq dir.
Let the fastq files be:

  • runID_control1_S1_L001_R1_001.fastq
  • runID_control2_S2_L001_R1_001.fastq
  • runID_treatment1_S3_L001_R1_001.fastq
  • runID_treatment2_S4_L001_R1_001.fastq

Let your STAR index files be in /data/star/human, the file truseq.fa.gz is provided by bbmap and is here symbolically linked to /data/resources/truseq.fa.gz.
The file /data/resources/polyA.fa.gz is a simple GNU-zipped fasta file containing a single entry with 18 ‘A’s.

#### use fastqc to check your data; please adjust the number of threads to your machine
fastqc --outdir qualitycheck --format fastq --threads 8 fastq/runID*

#### check the result with a browser
######## preparation for mapping
###go to fastq directory
cd fastq
### remove the adapter contamination, polyA read through, and low quality tails
for sample in runID*R1_001.fastq; do cat $i | in=stdin.fq out=${i}_trimmed_clean ref=/data/resources/polyA.fa.gz,/data/resources/truseq.fa.gz k=13 ktrim=r useshortkmers=t mink=5 qtrim=t trimq=10 minlength=20; done
### create symbolic links for better handling
### for-loops can be used according to name and structure
ln -s runID_control1_S1_L001_R1_001.fastq_trimmed_clean control1_R1.fastq
ln -s runID_treatment2_S4_L001_R12_001.fastq_trimmed_clean treatment2_R1.fastq

######### mapping
# create for each sample a folder in star_out/
cd ..
mkdir star_out
mkdir star_out/control1
mkdir star_out/control2

### run star

for sample in control1 control2 treatment1 treatment2 ; do \
STAR --runThreadN 8 --genomeDir /data/star/human --readFilesIn fastq/${sample}_R1.fastq \
--outFilterType BySJout --outFilterMultimapNmax 20 --alignSJoverhangMin 8 --alignSJDBoverhangMin 1 \
--outFilterMismatchNmax 999 --outFilterMismatchNoverLmax 0.1 --alignIntronMin 20 \
--alignIntronMax 1000000 --alignMatesGapMax 1000000 --outSAMattributes NH HI NM MD
--outSAMtype BAM SortedByCoordinate --outFileNamePrefix star_out/${sample} ;\

#Indexed bam files are necessary for many visualization and downstream analysis tools
cd star_out
for bamfile in */starAligned.sortedByCoord.out.bam ; do samtools index ${bamfile}; done

#From this point any further analysis can be applied.

1Goecks, J, Nekrutenko, A, Taylor, J and The Galaxy Team. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010 Aug 25;11(8):R86.