Ultra-low-depth Sequencing
Ultra-low-depth Sequencing - Related Videos
10:34
Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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Cited by 28 •
2019
Long-read sequences greatly facilitate the assembly of complex genomes and characterization of structural variation. We describe a method to generate ultra-long sequences by nanopore-based sequencing platforms. The approach adopts an optimized DNA extraction followed by modified library preparations to generate hundreds of kilobase reads with moderate coverage from human cells.
08:57
Amplicon Sequencing using the Long-Read Sequencing Technologies
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2025
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
07:59
Ultra-Fast Amplicon-Based Next-Generation Sequencing in Non-Squamous Non-Small Cell Lung Cancer
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Cited by 3 •
2023
The increase of molecular biomarkers to be tested for non-squamous non-small cell lung cancer (NS-NSCLC) care management has prompted the development of fast and reliable molecular detection methods. We describe a workflow for genomic alteration assessment for NS-NSCLC patients using an ultra-fast-next generation sequencing (NGS) approach.
01:27
Uniform Depth Channel Flow
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2025
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
01:15
Depth Perception and Spatial Vision
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2024
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
FAQs
Instead of interpreting each read as evidence about an individual nucleotide, researchers group aligned reads into defined genomic windows and compare the amount of sequence assigned to each region. Uneven representation across windows can indicate relative gains or losses of DNA. This window-based summary preserves genome-wide copy-number information even when coverage is insufficient for reliable base-by-base analysis.
Alignment places each sequence read at a corresponding location in a reference genome, allowing researchers to count reads consistently across genomic regions. Those regional counts provide the basis for estimating relative DNA representation and identifying broad abnormalities. Without this positional framework, sparse reads could not be converted into a genome-wide pattern of gains, losses, or uneven representation.
This approach is suited to broad genomic patterns, including copy-number changes, aneuploidy, and large-scale structural abnormalities. Its low read count does not reliably resolve every nucleotide or identify rare variants with the detail expected from conventional whole-genome sequencing. The method therefore supports screening and preliminary assessment rather than comprehensive, base-level characterization.
The workflow begins by fragmenting DNA, followed by sequencing the resulting fragments. Researchers then align the reads to a reference genome and aggregate them across genomic windows. Comparing read representation among those windows produces a genome-wide profile that can be evaluated for broad gains, losses, aneuploidy, or structural abnormalities.
It is useful when researchers need genome-wide screening without the expense or data volume of deep sequencing. In genetics, applications include examining tumors, embryos, and mixed populations for copy-number changes, aneuploidy, or large-scale structural abnormalities. These uses make the approach practical for broad genomic assessment when resolving rare or single-nucleotide variants is not the primary goal.
Its efficiency allows many samples to be surveyed for broad genomic patterns at lower cost than conventional whole-genome sequencing. Researchers can use the resulting window-level profiles to screen populations or perform an initial assessment of a sample before deciding whether deeper analysis is needed. The outcome is a scalable overview of genome-wide DNA representation, not a complete nucleotide-level sequence.