Improved sequence mapping using a complete reference genome and lift-over

Chen, Nae-Chyun; Paulin, Luis F; Sedlazeck, Fritz J.; Koren, Sergey; Phillippy, Adam M.; Langmead, Ben

doi:10.1101/2022.04.27.489683

Cited by 8 publications

(19 citation statements)

References 57 publications

(104 reference statements)

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“…We investigated the likelihood of these calls by restraining the mapping quality and assessing how this impacts the CN estimation. As previously reported, the alignment to the T2T-CHM13 reference results in less noisy and more reliable alignments for short reads 35 . Nevertheless, these T2T-CHM13 unique regions have specific challenges due to their repetitiveness 34 .…”

Section: Putative Gains In T2t-chm13 Specific Regions May Be Due To L...supporting

confidence: 65%

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

Kalef-Ezra,

Turan,

Perez-Rodriguez

et al. 2023

Preprint

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The presence of somatic mutations, including copy number variants (CNVs), in the brain is well recognized. Comprehensive study requires single-cell whole genome amplification, with several methods available, prior to sequencing. We compared PicoPLEX with two recent adaptations of multiple displacement amplification (MDA): primary template-directed amplification (PTA) and droplet MDA, across 93 human brain cortical nuclei. We demonstrated different properties for each, with PTA providing the broadest amplification, PicoPLEX the most even, and distinct chimeric profiles. Furthermore, we performed CNV calling on two brains with multiple system atrophy and one control brain using different reference genomes. We found that 38% of brain cells have at least one Mb-scale CNV, with some supported by bulk sequencing or single-cells from other brain regions. Our study highlights the importance of selecting whole genome amplification method and reference genome for CNV calling, while supporting the existence of somatic CNVs in healthy and diseased human brain.

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Section: Putative Gains In T2t-chm13 Specific Regions May Be Due To L...supporting

confidence: 65%

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

Kalef-Ezra,

Turan,

Perez-Rodriguez

et al. 2023

Preprint

Self Cite

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“…translated into GRCh38 coordinates. We call the second method – the one that uses both T2T-CHM13 and GRCh38 – the “LevioSAM 2” method, since it was first proposed in the LevioSAM 2 study by Chen et al [5].…”

Section: Resultsmentioning

confidence: 99%

Measuring, visualizing and diagnosing reference bias with biastools

Lin,

Iyer,

Chen

et al. 2023

Preprint

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A goal of recent alignment methods is to reduce reference bias, which occurs when reads containing non-reference alleles fail to align to their true point of origin. However, there is a lack of methods for systematically measuring, categorizing, and diagnosing reference bias. We present biastools, which analyzes and categorizes instances of reference bias. Biastools has different sets of functionality tailored to different scenarios, i.e. (a) when the donor genome is well-characterized and input reads are simulated, (b) when the donor is well-characterized and reads are real, and (c) when the donor is not well-characterized and reads are real. When possible, biastools divides instances of reference bias into categories according to their cause: bias due to loss, flux, or local misalignment. Biastools' scan mode detects large-scale mapping artifacts due to structural variation and flaws in the reference representation. Our findings confirm that including more variants in a graph genome alignment method results in fewer reference biases. We also find that end-to-end alignment modes are effective in reducing bias at insertions and deletions, compared to local aligners that allow soft clipping. Finally, we use biastools to characterize the ways in which using the new telomere-to-telomere human reference can improve bias at a large scale. In short, biastools is a tool uniquely focused on reference bias, making it a valuable resource as the field continues to develop new aligners and pangenome representations to reduce bias.

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“…Improvements in computational performance have already been demonstrated through graph-simplification and the development of more advanced mapping and variant identification models, [80][81][82] with further improvements expected. 83 While alternatives to graph-based alignment which leverage multiple reference sequences have also been developed, such as alignment using multiple linear references in tandem, 84,85 their performance has not been assessed using HBV sequencing data. Furthermore, an added benefit of graph-based approaches is that differences observed between the embedded paths/reference sequences can be utilized during variant calling to identify loci of genetic variation, in addition to mutations inferred from the alignment of sequencing data directly.…”

Section: Discussionmentioning

confidence: 99%

A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV

Duchen

Clipman

Vergara

et al. 2023

Preprint

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Hepatitis B virus (HBV) remains a global public health concern, with over 250 million individuals living with chronic HBV infection (CHB) and no curative therapy currently available. Viral diversity is associated with CHB pathogenesis and immunological control of infection. Improved methods to characterize the viral genome at both the population and intra-host level could aid drug development efforts. Conventionally, HBV sequencing data are aligned to a linear reference genome and only sequences capable of aligning to the reference are captured for analysis. Reference selection has additional consequences, including sample-specific 'consensus' sequence construction. It remains unclear how to select a reference from available sequences and whether a single reference is sufficient for genetic analyses. Using simulated short-read sequencing data generated from full-length publicly available HBV genome sequences and HBV sequencing data from a longitudinally sampled individual with CHB, we investigate alternative graph-based alignment approaches. We demonstrate that using a phylogenetically representative 'genome graph' for alignment, rather than linear reference sequences, avoids issues of reference ambiguity, improves alignment, and facilitates the construction of sample-specific consensus sequences genetically similar to an individual's infection. Graph-based methods can therefore improve efforts to characterize the genetics of viral pathogens, including HBV, and may have broad implications in host pathogen research.

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Improved sequence mapping using a complete reference genome and lift-over

Cited by 8 publications

References 57 publications

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

Single-cell somatic copy number variants in brain using different amplification methods and reference genomes

Measuring, visualizing and diagnosing reference bias with biastools

A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV

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