HQAlign: aligning nanopore reads for SV detection using current-level modeling.

MOTIVATION: Detection of structural variants (SVs) from the alignment of sample DNA reads to the reference genome is an important problem in understanding human diseases. Long reads that can span repeat regions, along with an accurate alignment of these long reads play an important role in identifying novel SVs. Long-read sequencers, such as nanopore sequencing, can address this problem by providing very long reads but with high error rates, making accurate alignment challenging. Many errors induced by nanopore sequencing have a bias because of the physics of the sequencing process and proper utilization of these error characteristics can play an important role in designing a robust aligner for SV detection problems. In this article, we design and evaluate HQAlign, an aligner for SV detection using nanopore sequenced reads. The key ideas of HQAlign include (i) using base-called nanopore reads along with the nanopore physics to improve alignments for SVs, (ii) incorporating SV-specific changes to the alignment pipeline, and (iii) adapting these into existing state-of-the-art long-read aligner pipeline, minimap2 (v2.24), for efficient alignments. RESULTS: We show that HQAlign captures about 4%-6% complementary SVs across different datasets, which are missed by minimap2 alignments while having a standalone performance at par with minimap2 for real nanopore reads data. For the common SV calls between HQAlign and minimap2, HQAlign improves the start and the end breakpoint accuracy by about 10%-50% for SVs across different datasets. Moreover, HQAlign improves the alignment rate to 89.35% from minimap2 85.64% for nanopore reads alignment to recent telomere-to-telomere CHM13 assembly, and it improves to 86.65% from 83.48% for nanopore reads alignment to GRCh37 human genome. AVAILABILITY AND IMPLEMENTATION: https://github.com/joshidhaivat/HQAlign.git.

Impact of Potential Symptoms and Risks Associated with Acid Sphingomyelinase Deficiency on Patients and Caregivers: A Best-Worst Scaling Study.

Purpose: Acid sphingomyelinase deficiency (ASMD) is a rare, progressive, and potentially fatal disease affecting major organs; its symptoms present heterogeneously. Data on the most bothersome symptoms for patients with ASMD types B or A/B and their caregivers or parents are limited. We conducted a survey to quantify the relative impact of potential ASMD symptoms and risks for patients and parents/caregivers. Patients and Methods: Twenty respondents, recruited via National Niemann-Pick Disease Foundation (United States) and Niemann-Pick United Kingdom, took a preference survey: 11 patients who had a self-reported diagnosis of ASMD types B or A/B and 9 parents who had a child with ASMD types B or A/B. Using object-case best-worst scaling, we explored the most and least bothersome among a set of 15 ASMD symptoms/risks selected based on clinical input and qualitative research with patients and caregivers. In 15 experimentally designed questions containing five items each, respondents ranked the symptoms/risks, irrespective of their experiences with them. Data were analyzed using a conditional multinomial logit model. Results: Patients reported constant abdominal pain, severe pain in bones and joints, and severe fatigue to be the most bothersome potential symptoms or risks, followed by a chance of bleeding in the spleen. The next most bothersome potential symptom was constant shortness of breath. Easy bruising and noticeable abdominal enlargement were among the least bothersome symptoms. The most bothersome symptom for parents was bleeding in the spleen. Conclusion: Patients and parents had similar perceptions of the most bothersome potential symptoms/risks. Despite the small sample size typical of rare disease studies, understanding patient preferences is important for such diseases and can inform shared decision-making.

HQAlign: Aligning nanopore reads for SV detection using current-level modeling.

Motivation: Detection of structural variants (SV) from the alignment of sample DNA reads to the reference genome is an important problem in understanding human diseases. Long reads that can span repeat regions, along with an accurate alignment of these long reads play an important role in identifying novel SVs. Long read sequencers such as nanopore sequencing can address this problem by providing very long reads but with high error rates, making accurate alignment challenging. Many errors induced by nanopore sequencing have a bias because of the physics of the sequencing process and proper utilization of these error characteristics can play an important role in designing a robust aligner for SV detection problems. In this paper, we design and evaluate HQAlign, an aligner for SV detection using nanopore sequenced reads. The key ideas of HQAlign include (i) using basecalled nanopore reads along with the nanopore physics to improve alignments for SVs (ii) incorporating SV specific changes to the alignment pipeline (iii) adapting these into existing state-of-the-art long read aligner pipeline, minimap2 (v2.24), for efficient alignments. Results: We show that HQAlign captures about 4 - 6% complementary SVs across different datasets which are missed by minimap2 alignments while having a standalone performance at par with minimap2 for real nanopore reads data. For the common SV calls between HQAlign and minimap2, HQAlign improves the start and the end breakpoint accuracy for about 10 - 50% of SVs across different datasets. Moreover, HQAlign improves the alignment rate to 89.35% from minimap2 85.64% for nanopore reads alignment to recent telomere-to-telomere CHM13 assembly, and it improves to 86.65% from 83.48% for nanopore reads alignment to GRCh37 human genome. Availability: https://github.com/joshidhaivat/HQAlign.git.

HQAlign: Aligning nanopore reads for SV detection using current-level modeling.

MOTIVATION: Detection of structural variants (SV) from the alignment of sample DNA reads to the reference genome is an important problem in understanding human diseases. Long reads that can span repeat regions, along with an accurate alignment of these long reads play an important role in identifying novel SVs. Long read sequencers such as nanopore sequencing can address this problem by providing very long reads but with high error rates, making accurate alignment challenging. Many errors induced by nanopore sequencing have a bias because of the physics of the sequencing process and proper utilization of these error characteristics can play an important role in designing a robust aligner for SV detection problems. In this paper, we design and evaluate HQAlign, an aligner for SV detection using nanopore sequenced reads. The key ideas of HQAlign include (i) using basecalled nanopore reads along with the nanopore physics to improve alignments for SVs (ii) incorporating SV specific changes to the alignment pipeline (iii) adapting these into existing state-of-the-art long read aligner pipeline, minimap2 (v2.24), for efficient alignments. RESULTS: We show that HQAlign captures about 4%-6% complementary SVs across different datasets which are missed by minimap2 alignments while having a standalone performance at par with minimap2 for real nanopore reads data. For the common SV calls between HQAlign and minimap2, HQAlign improves the start and the end breakpoint accuracy for about 10%-50% of SVs across different datasets. Moreover, HQAlign improves the alignment rate to 89.35% from minimap2 85.64% for nanopore reads alignment to recent telomere-to-telomere CHM13 assembly, and it improves to 86.65% from 83.48% for nanopore reads alignment to GRCh37 human genome.

Impact and burden of acid sphingomyelinase deficiency from a patient and caregiver perspective.

Acid sphingomyelinase deficiency (ASMD), historically known as Niemann-Pick disease (NPD) types A, A/B, and B, is a rare, progressive, potentially fatal lysosomal storage disease with a spectrum of phenotypes. Little is known about how ASMD symptoms affect the lives of patients and their caregivers. In a cross-sectional qualitative study conducted in the US and UK, and in collaboration with the National Niemann-Pick Disease Foundation (US) and Niemann-Pick UK, we investigated the symptom experience of patients with ASMD types B and A/B and explored how the disease impacts their and their caregivers' lives. The study included 17 adult patients (mean age 38.7 years, 12 female), three caregivers of adults with ASMD, 12 pediatric/adolescent patients with ASMD (mean age 10.5 years, six female), and 12 caregivers of pediatric/adolescent patients with ASMD. The most commonly reported disease manifestations were respiratory (n = 26, 89.7%), abdominal (n = 25, 86.2%), and musculoskeletal symptoms (n = 23, 79.3%); excessive bleeding or bruising (n = 20, 69%); fatigue (n = 20, 69%); gastrointestinal symptoms (n = 18, 62.1%); and headache (n = 15, 51.7%). ASMD was reported to negatively impact patients' physical function (n = 23, 79.3%), self-esteem (n = 18, 62.1%), emotions (n = 16, 55.2%), social function and relationships (n = 16, 55.2%), and personal care (n = 9, 31%). Providing care for individuals with ASMD negatively affected caregivers' emotional well-being (n = 12, 80%), social function (n = 4, 26.7%), relationships (n = 6, 40%), and financial security (n = 7, 46.7%). The physical toll of providing care, the need for lifestyle changes, and the responsibility for making medical decisions added to the burden for caregivers. Alternatively, some caregivers noted that caring for a loved one enhanced their spirituality, providing them with a different outlook on life and a deeper personal resolve. This study showed that ASMD is a substantial burden for patients and caregivers, with long-term physical, emotional, social, and financial impacts. The study confirmed commonly known manifestations of ASMD, especially respiratory problems, but also identified less recognized ones, such as dermatological complications. The data collected and insight gained from this study should enhance clinical care, help evaluate new treatments, and inform health care decision making for patients with ASMD.

QAlign: aligning nanopore reads accurately using current-level modeling.

MOTIVATION: Efficient and accurate alignment of DNA/RNA sequence reads to each other or to a reference genome/transcriptome is an important problem in genomic analysis. Nanopore sequencing has emerged as a major sequencing technology and many long-read aligners have been designed for aligning nanopore reads. However, the high error rate makes accurate and efficient alignment difficult. Utilizing the noise and error characteristics inherent in the sequencing process properly can play a vital role in constructing a robust aligner. In this article, we design QAlign, a pre-processor that can be used with any long-read aligner for aligning long reads to a genome/transcriptome or to other long reads. The key idea in QAlign is to convert the nucleotide reads into discretized current levels that capture the error modes of the nanopore sequencer before running it through a sequence aligner. RESULTS: We show that QAlign is able to improve alignment rates from around 80% up to 90% with nanopore reads when aligning to the genome. We also show that QAlign improves the average overlap quality by 9.2, 2.5 and 10.8% in three real datasets for read-to-read alignment. Read-to-transcriptome alignment rates are improved from 51.6% to 75.4% and 82.6% to 90% in two real datasets. AVAILABILITY AND IMPLEMENTATION: https://github.com/joshidhaivat/QAlign.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The prevalence of complications associated with lumbar and thoracic spinal deformity surgery in the elderly population: a meta-analysis.

BACKGROUND: The prevalence of spinal deformities increases with age, affecting between 30% and 68% of the elderly population (ages ≥65). The reported prevalence of complications associated with surgery for spinal deformities in this population ranges between 37% and 71%. Given the wide range of reported complication rates, the decision to perform surgery remains controversial. METHODS: A comprehensive search was conducted using PubMed, Embase, and Cochrane to identify studies reporting complications for spinal deformity surgery in the elderly population. Pooled prevalence estimates for individual complication types were calculated using the random-effects model. RESULTS: Of 5,586 articles, 14 met inclusion criteria. Fourteen complication types were reported, with at least 2 studies for each complication with the following pooled prevalence: reoperation (prevalence 19%; 95% CI, 9-36%; 107 patients); hardware failure (11%; 95% CI, 5-25%; 52 patients); infection (7%; 95% CI, 4-12%; 262 patients); pseudarthrosis (6%; 95% CI, 3-12%; 149 patients); radiculopathy (6%; 95% CI, 1-33%; 116 patients); cardiovascular event (5%; 95% CI, 1-32%; 121 patients); neurological deficit (5%; 95% CI, 2-15%; 248 patients); deep vein thrombosis (3%; 95% CI, 1-7%; 230 patients); pulmonary embolism (3%; 95% CI, 1-7%; 210 patients); pneumonia (3%; 95% CI, 1-11%; 210 patients); cerebrovascular or stroke event (2%; 95% CI, 0-9%; 85 patients); death (2%; 95% CI, 1-9%; 113 patients); myocardial infarction (2%; 95% CI, 1-6%; 210 patients); and postoperative hemorrhage (1%; 95% CI, 0-10%; 85 patients). CONCLUSIONS: Most complication types following spinal deformity surgery in the elderly had prevalence point estimates of <6%, while all were at least ≤19%. Additional studies are needed to further explore composite prevalence estimates and prevalence associated with traditional surgical approaches as compared to minimally-invasive procedures in the elderly.