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Quizzes > Quizzes for Business > Technology

Take the NGS Technology Knowledge Quiz

Assess Your Next-Gen Sequencing Skills Today

Difficulty: Moderate
Questions: 20
Learning OutcomesStudy Material
Colorful paper art promoting a fun NGS Technology Knowledge Quiz.

Ready to master next-generation sequencing? This NGS Technology Knowledge Quiz challenges you with targeted practice questions on genomics principles and data workflows. Ideal for students, lab technicians, or educators looking for a focused Technology Knowledge Quiz or supplemental Technology Skills Assessment Quiz. Each question is fully editable - customise it in our editor anytime via the quizzes page to tailor the experience to your learning goals.

Which file format commonly used in NGS contains both nucleotide sequences and their corresponding quality scores?
FASTQ
FASTA
BAM
VCF
The FASTQ format stores both the nucleotide sequence and per-base quality scores. This dual storage makes it the standard input for many downstream NGS analysis tools. FASTA stores only sequences, BAM is a binary alignment file, and VCF records variants.
Which sequencing technology is based on the principle of sequencing by synthesis and widely used for high-throughput short reads?
PacBio SMRT
Oxford Nanopore
Sanger
Illumina
Illumina platforms use sequencing by synthesis chemistry to generate millions of short reads in parallel. This approach underpins most high-throughput NGS workflows. Other technologies use different principles, such as single-molecule real-time or nanopore-based detection.
In an Illumina sequencing workflow, what is the purpose of the cluster generation step?
Amplifying library fragments on the flow cell to form clusters
Converting analog signals to digital base calls
Removing adapter dimers from the library
Aligning reads to a reference genome
Cluster generation uses bridge amplification to produce millions of copies of each library fragment on the flow cell. This amplification is essential for generating detectable sequencing signals. It is distinct from alignment or base calling steps.
Why are adapters ligated to DNA fragments during NGS library preparation?
To increase GC content of fragments
To fluorescently label the DNA fragments
To degrade non-target DNA
To facilitate binding and priming on the sequencing platform
Adapters contain sequences required for flow cell binding and priming of the sequencing reaction. They also often include index sequences for multiplexing. They do not alter GC content or label fragments directly.
What does paired-end sequencing enable compared to single-end sequencing?
It sequences the same fragment twice from the same end
It doubles the read length of each individual read
It sequences RNA instead of DNA
It reads both ends of each DNA fragment, improving alignment
Paired-end sequencing reads DNA fragments from both ends, which improves mapping accuracy and detection of structural variants. It does not inherently double read length or switch molecule type.
How is a PHRED quality score (Q) related to the probability of an incorrect base call (P)?
Q = 10 log10(P)
Q = -10 log10(P)
Q = P / 10
Q = -10 P
PHRED quality scores are defined as Q = -10 Ã - log10(P), where P is the error probability. This scale allows easier interpretation: a higher Q means a lower chance of error. Other formulas do not follow the PHRED definition.
What is the primary purpose of spiking a PhiX control library into an Illumina sequencing run?
To replace index primers in multiplexing
To calibrate base calling in nanopore sequencing
To increase sample diversity on low-complexity libraries
To remove adapter dimers during sequencing
PhiX provides a balanced and well-characterized library that helps calibrate base calling, especially when sequencing low-complexity or amplicon libraries. It is not used in nanopore platforms or to remove adapters.
Which FastQC report module is used to detect biases in GC content across reads?
Adapter Content
Kmer Content
GC Content
Per Sequence Quality Scores
The GC Content module plots the observed GC distribution across all reads against a theoretical distribution. This helps identify GC bias in the library. Other modules assess quality scores, k-mers, or adapter contamination.
Which DNA fragmentation method uses acoustic energy to shear DNA into random fragments?
Sonication
Nebulization
PCR amplification
Restriction enzyme digestion
Sonication uses ultrasonic waves to physically shear DNA into random fragments of various sizes. Nebulization uses compressed air, while restriction enzymes cut at specific sequences. PCR amplifies existing fragments.
Which alignment tool is commonly used for mapping short Illumina reads to a reference genome?
BWA
MAFFT
BLAST
Clustal Omega
BWA (Burrows-Wheeler Aligner) is optimized for high-throughput mapping of short reads to a reference genome. BLAST is for general sequence similarity searches, while MAFFT and Clustal Omega are multiple sequence alignment tools.
What is the goal of demultiplexing in a multiplexed sequencing run?
Removing low-quality reads from the dataset
Trimming adapter sequences
Assigning reads to samples based on barcode sequences
Filtering out duplicate reads
Demultiplexing sorts reads into individual sample files according to unique index or barcode sequences. It does not perform quality trimming or duplicate filtering.
In a typical variant calling pipeline, which tool is often used to mark duplicate reads before calling variants?
BWA MEM
GATK HaplotypeCaller
Picard MarkDuplicates
FastQC
Picard's MarkDuplicates identifies and flags duplicate reads that arise from PCR amplification. This prevents counting them as independent observations during variant calling. HaplotypeCaller performs the calling itself.
In a VCF file, which INFO field indicates the total depth of reads supporting the variant?
DP
QUAL
MQ
AF
The DP field in the INFO column of a VCF record gives the total number of reads covering the position. QUAL is a quality score for the variant call, MQ is mapping quality, and AF is allele frequency.
What does a low mapping quality (MAPQ) score typically indicate about a read alignment?
Alignment to multiple locations or low confidence
High confidence unique alignment
Perfect match to the reference
Read is shorter than expected
A low MAPQ score usually means the aligner found multiple equally good positions for that read or has low confidence. High MAPQ indicates a unique, high-confidence placement.
Which factor can help reduce GC bias during PCR amplification in library preparation?
Using higher denaturation temperature
Adding betaine or DMSO to the reaction
Eliminating adapter ligation step
Increasing PCR cycle number
Additives such as betaine or DMSO help destabilize GC-rich secondary structures, leading to more uniform amplification across GC extremes. Changing PCR cycles or skipping adapters does not address GC bias.
If a sequencing run shows a high rate of duplicate reads, what is a likely cause and solution?
Low cluster density; increase input DNA concentration
Over-amplification during PCR; reduce PCR cycles
High base calling error rate; recalibrate quality scores
Incorrect adapter ligation; redesign adapters
Excessive PCR cycles during library prep can cause over-amplification, leading to many duplicate reads. Reducing the number of PCR cycles lowers duplication and increases library complexity.
Compared to Illumina sequencing, Oxford Nanopore sequencing is more prone to which type of error?
Bridge amplification artifacts
Fluorescence signal bleed-through
Single-base substitutions
Insertions and deletions
Nanopore sequencing signal interpretation often struggles with homopolymer regions, resulting in insertion and deletion errors. Illumina primarily has substitution errors and uses fluorescence-based detection.
When optimizing fragment size for de novo genome assembly, which insert size range is generally most beneficial for Illumina paired-end reads?
50-100 bp
200-400 bp
5000-10000 bp
1000-2000 bp
Insert sizes of about 200 - 400 bp allow sufficient overlap between paired-end reads for high-quality assembly and scaffolding. Very small or very large inserts reduce assembly contiguity or coverage efficiency.
In multiplexed runs on patterned flow cells, index hopping can lead to misassignment of reads; which strategy best mitigates this issue?
Increasing cluster amplification time
Using single-end sequencing only
Employing unique dual indexes
Lowering denaturation temperature
Unique dual indexing uses distinct barcodes on both ends of each fragment, making index hopping events easily identifiable and filterable. Other strategies do not effectively address misassigned indexes.
In variant calling, the allele frequency (AF) field denotes what information?
The ratio of reads supporting the variant allele to total reads
The GC content at the variant site
The average depth across all samples
The Phred-scaled quality of the variant call
The AF field indicates the fraction of sequencing reads at that position that carry the variant allele, helping distinguish between homozygous, heterozygous, or subclonal variants. It is not a quality or depth metric.
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Learning Outcomes

  1. Analyse next-generation sequencing workflows and data outputs
  2. Identify major NGS platforms and sequencing methodologies
  3. Evaluate sequence quality metrics and troubleshooting approaches
  4. Apply best practices for library preparation and sample handling
  5. Interpret alignment results and variant calling outputs

Cheat Sheet

  1. Mastering NGS Workflow Steps - Jump into the heart of NGS by understanding the four core stages: nucleic acid extraction, library preparation, sequencing, and data analysis. Each step is a vital level in your sequencing adventure, so nail them all for top-notch results! NGS Workflow Steps
  2. Exploring Major NGS Platforms - Get to know the heavy hitters of sequencing: Illumina's synthesis, Ion Torrent's semiconductor approach, and PacBio's real-time reads. Each platform brings its own flavor to the lab, so pick the best tool for your research mission! Comparison of High-Throughput Sequencing Methods
  3. Decoding Sequencing Methodologies - Dive into WGS, WES, and targeted sequencing to see how coverage and focus can shift your research outcomes. Whether you want the whole genome panorama or a zoomed-in exome snapshot, choosing the right method is key! DNA Sequencing Methods
  4. Cracking Sequence Quality Metrics - Learn why Phred scores are your best friends when judging read accuracy, and how a few low-quality bases can turn your data upside down. High scores mean high confidence - never ignore your quality checks! Phred Quality Score
  5. Troubleshooting NGS Challenges - Discover common hiccups in library prep, run errors, and analysis snags before they derail your project. A solid troubleshooting playbook keeps your data clean and your experiments on track! Next-Generation Sequencing Technologies
  6. Perfecting Library Preparation - Master DNA fragmentation, adapter ligation, and amplification so your libraries are always sequencing-ready. A flawless prep means fewer reruns and more time celebrating awesome data! NGS Library Preparation
  7. Nailing Sample Handling - Keep contamination and degradation at bay with rock-solid storage, extraction, and quantification protocols. Treat your samples like gold - good handling today means reliable results tomorrow! Sample Preparation for NGS
  8. Interpreting Alignment Results - Learn to read mapping quality, coverage depth, and alignment scores like a pro detective. Accurate alignment sets the stage for trustworthy downstream analyses! Alignment and Mapping
  9. Navigating Variant Calling - Uncover SNVs, insertions, deletions, and structural variants by mastering popular calling algorithms. Understanding the strengths and quirks of each tool will give your discoveries more power! Variant Discovery
  10. Keeping Up with NGS Innovations - Stay ahead of the curve by tracking advances in read length, accuracy, and throughput. New tech drops fast - keeping current means you'll always choose the best approach for your next big experiment! Next-Generation Sequencing Technology
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