HiSeq 4000, NovaSeq multiplex sample issues

https://med.stanford.edu/gssc/hiseq4000issue.html

https://enseqlopedia.com/2016/12/index-mis-assignment-between-samples-on-hiseq-4000-and-x-ten/

 

 If free barcoded adapter / index primers are present in a multiplexed pool, the free adapter has the potential to prime and extend library molecules in the same lane during the clustering step.  This can result in mis-assignment of reads through index swapping.  This can cause errors in demultiplexing data, as reads from one sample have the potential to end up in the FASTQ files of a different sample.  The HiSeq 2000/2500 and MiSeq are less impacted due to their biochemistry and the geometry of the flow cell used.

 

The range of mis-assignment can vary significantly and is impacted by the following factors:

• Amount of free adapter present in library
• Storage conditions of library
• Application or library prep workflow

 

Sample mis-assignment can potentially impact users depending on the experimental design and library prep workflow.  Illumina has been working on this issue internally and has developed a few suggested mitigation strategies to reduce index swaps, listed below:

During Library Construction:

• Optimize your PCR or ligation step to avoid an excess of adapters or index primers.
• For PCR dilute the index primers to adjust the insert to adapter / primer ratio.
• Perform extra clean ups after this step.
• PAGE purification seems to do a good job reducing indexing primers.
• Purification columns are also an option.
• Do extra clean ups of each individual library before pooling.
• Use single use aliquoted adapters and primers.
• Freeze individual libraries and pool prior to sequencing.

Pooling suggestions:

• Use dual indexing strategies with unique barcodes on both ends. (Swapping would have to occur at both ends for read mis-assignment to occur)
• Sequence or freeze created libraries pools as soon as possible.

Sequencing suggestions:

• Use PhiX from third parties with unique indexing barcodes to determine swap frequency. (We will have begun to introduce PhiX with unique barcodes from SeqMatic for HiSeq 4000 runs.)
• For methods highly sensitive to mis-assignment use HiSeq 2000/2500 or MiSeq instruments.

 

MiSeq, HiSeq, NovaSeq read output tables

 https://med.stanford.edu/gssc/services/sequencing1.html

 

Illumina Sequencing Services

	MiSeq	MiSeq Micro	HiSeq 4000	iSeq 100	NovaSeq 6000 SP	NovaSeq 6000 S1	NovaSeq 6000 S2	NovaSeq 6000 S4
Run Time	4-56 hours	24 hours	2-4 days	9-17.5 hours	13-38 hours	13-25 hours	16-36 hours	36-44 hours
Maximum Output	15 Gb	1.2 Gb	1500 Gb	1.2 Gb	325-400 Gb	400-500 Gb	1000-1250 Gb	2400-3000 Gb
Average Read Output	22 - 25 million	4 million	250 - 400 million	4 million	325 - 400 million	750 - 800 million	1,650 - 2,050 million	2,000 - 2,500 million
Maximum Read Length	2 x 300 bp	2 x 150 bp	2 x 150 bp	2 x 150 bp	2 x 250 bp	2 x 150 bp	2 x 150 bp	2 x 150 bp

UMI (Unique Molecular Identifier)

 https://dnatech.genomecenter.ucdavis.edu/faqs/what-are-umis-and-why-are-they-used-in-high-throughput-sequencing/

 UMI

also known as 'Molecular Barcodes'

 Quantitative sequencing analysis

- can be used in removal of PCR duplicate 

Genomic variant detection

HiSeq, MiSeq, NovaSeq : Read length, # of cluster per lane, Base per lane

https://medicine.yale.edu/keck/ycga/sequencing/illumina/hiseq.aspx

Sequencer	Read length	# of Clusters per lane (millions)	Bases per lane (Gbp)
HiSeq 2500 Rapid	1x75	150	11.25
HiSeq 2500 Rapid	2x75	150	22.5
HiSeq 2500 Rapid	2x150	150	45
HiSeq 2500 High-output	1x75	200	15
HiSeq 2500 High-output	2x75	200	30
HiSeq 4000	2x100	300	60
HiSeq 4000	2x150	300	90
NovaSeq S2	2x100	1650	330
NovaSeq S2	2x150	1650	500
NovaSeq S4	2x150	2000	600

https://www.fasteris.com/dna/?q=node/41

Illumina HiSeq Services:

Service Type	Run (Mode)	Number of pass filter clusters (1)	Yield (1)	Sequencing Run Time (2)
HiSeq 4000 (3) - 1x lane	1x50 bp	Up to 350 million, average yield 280-300 mio (*)	17.5 Gb	1 - 4 days
	1x150 bp		52.5 Gb
	2x75 bp		52.5 Gb
	2x150 bp		105 Gb
HiSeq 2500, v4 (4)  - 1x lane	2x125 bp	Up to 280 million, average yield 240-260 mio (*)	70 Gb	8 days
HiSeq 2500 Rapid Run, v2 - 1x flow cell run	1x50 bp	Up to 300 million, average yield 240-260 mio (*)	15 Gb	1 - 3 days
	1x125 bp		37.5 Gb
	2x50 bp		30 Gb
	2x125 bp		75 Gb
	2x250 bp		150 Gb
	2x300 bp		180 Gb
1x test run (done on MiSeq Nano) (5)	1x50 bp	500'000 to 1 million reads	50 Mb	+ 4 days
1x test run (done on MiSeq Nano) (5)	1x150 bp	500'000 to 1 million reads	150 Mb	+ 4 days
(1) All the calculations have been made with specifications and typical Fasteris results when using optimized loading conditions. Individual results may vary. (2) This time is the "pure" running time of the system and includes time for washing. Not included is the time for doing the entry QC, library preparation, collection of other lane projects and/or the time for de-multiplexing of the derived data files. (3) On HiSeq 4000, we typically can reach 300-320 million passed-filter DNA clusters, up to 350 million or more pass filter DNA clusters per lane. (4) On HiSeq 2500 we typically can reach 250-280 million passed-filter DNA clusters per lane. For libraries with a test run done, we guarantee a minimum of 250 million pass filter DNA clusters per lane. (5) A test sequencing run is an extra service step needed to be ordered when min guaranteed data output and min guaranteed data yield is needed, especially for sequencing of customer-provided ready-to-run (RTR) libraries. (*) Average yields are given by statistic analysis of our runs; not included are biased or non-standard samples. Conditions and Details are subject to changes without notice.

https://www.illumina.com/systems/sequencing-platforms/miseq/specifications.html

Cluster Generation and Sequencing

	MiSeq Reagent Kit v2				MiSeq Reagent Kit v3
Read Length	1 × 36 bp	2 × 25 bp	2 × 150 bp	2 × 250 bp	2 × 75 bp	2 × 300 bp
Total Time*	~4 hrs	~5.5 hrs	~24 hrs	~39 hrs	~21 hrs	~56 hrs
Output	540–610 Mb	750–850 Mb	4.5–5.1 Gb	7.5–8.5 Gb	3.3–3.8 Gb	13.2–15 Gb

	MiSeq Reagent Kit v2 Micro	MiSeq Reagent Kit v2 Nano
Read Length	2 × 150 bp	2 × 250 bp	2 × 150 bp
Total Time*	~19 hrs	~28 hrs	~17 hrs
Output	1.2 Gb	500 Mb	300 Mb

* Total time includes cluster generation, sequencing, and base calling on a MiSeq System enabled with dual-surface scanning.

Reads Passing Filter^**

	MiSeq Reagent Kit v2	MiSeq Reagent Kit v3	MiSeq Reagent Kit v2 Micro	MiSeq Reagent Kit v2 Nano
Single Reads	12-15 million	22–25 million	4 million	1 million
Paired-End Reads	24–30 million	44–50 million	8 million	2 million

  ** Install specifications based on Illumina PhiX control library at supported cluster densities (865-965 k/mm² clusters passing filter for v2 chemistry and 1200-1400 k/mm² clusters passing filter for v3 chemistry). Actual performance parameters may vary based on sample type, sample quality, and clusters passing filter.

 

things to install for NGS analysis

NCURSE -programming library for text-based user interfaces
 http://codybonney.com/installing-the-ncurses-library-in-centos-6-5/

 sudo yum install ncurses-devel


Cutadapt - adapter sequence trimming
 http://cutadapt.readthedocs.org/en/latest/index.html

Trimmomatic: A flexible read trimming tool for Illumina NGS data
 http://www.usadellab.org/cms/?page=trimmomatic

FastQC - quality check of fastq file
 http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

Bowtie - short read aligner
 http://bowtie-bio.sourceforge.net/index.shtml
 http://bowtie-bio.sourceforge.net/bowtie2/index.shtml

Tophat - splice junction mapper for RNA-Seq reads (need Bowtie)
 https://ccb.jhu.edu/software/tophat/index.shtml

samtools - tools for manipulating alignments in the SAM(Sequence Alignment/Map) format,
 http://samtools.sourceforge.net/

picard -  tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF
 http://broadinstitute.github.io/picard/

HTSeq - Python package that provides infrastructure to process data from high-throughput sequencing assays
 http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html

MACS - Model-based Analysis for ChIP-Seq
 http://liulab.dfci.harvard.edu/MACS/

PeakSplitter - Subdivision of ChIP-seq/ChIP-chip regions into discrete signal peaks
 http://www.ebi.ac.uk/research/bertone/software

R -  free software environment for statistical computing and graphics
 https://www.r-project.org/

IGV - Integrative Genomics Viewer
 https://www.broadinstitute.org/igv/
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