scholarly journals MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection

2020 ◽  
Author(s):  
Phuc-Loi Luu ◽  
Phuc-Thinh Ong ◽  
Tran Thai Huu Loc ◽  
Dilys Lam ◽  
Ruth Pidsley ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Performance ◽  
Complete Analysis ◽  
Disease Detection ◽  
Analysis Tool ◽  
Clinical Implementation ◽  
Sequencing Data ◽  
Fresh Tissue ◽  
Interactive Analysis ◽  
Parallel Pipeline

AbstractBackgroundMultiplex bisulphite PCR sequencing is a convenient and scalable method to comprehensively profile DNA methylation at selected loci. The method is useful for validation of methylation biomarker panels on large clinical cohorts, as it can be applied to DNA isolated from fresh tissue, archival formalin fixed paraffin embedded tissue (FFPET) or circulating cell free DNA in plasma. However, successful clinical implementation of DNA methylation biomarkers for disease detection using multiplex bisulphite PCR sequencing, requires user-friendly sample analysis methods and a diversity of visualisation options, which are not met by current tools.ResultsWe have developed a computational pipeline with an interactive graphical interface, called MethPanel, in order to rapidly analyse multiplex bisulphite PCR sequencing data. MethPanel comprises a complete analysis workflow from genomic alignment to DNA methylation calling and supports an unlimited number of PCR amplicons and input samples. Moreover, MethPanel offers important and unique features, such as calculation of a polymorphism score and bisulphite PCR bias correction capabilities. MethPanel is designed so that the methylation data from all samples can be run in parallel on either a personal computer or a high performance computer. The outputs are also automatically forwarded to a shinyApp for convenient display, visualisation and sharing data with collaborators and clinicians. Importantly the data is centralised in one location, which aids storage management.Availability and ImplementationMethPanel is freely available at https://github.com/thinhong/MethPanelConclusionMethPanel provides a novel parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation marker panels for disease detection.

scholarly journals MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection

2020 ◽  
Author(s):  
Phuc-Loi Luu ◽  
Phuc-Thinh Ong ◽  
Tran Thai Huu Loc ◽  
Dilys Lam ◽  
Ruth Pidsley ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Supplementary Information ◽  
Complete Analysis ◽  
Analysis Tool ◽  
Sequencing Data ◽  
Interactive Analysis ◽  
Disease States ◽  
Parallel Pipeline ◽  
Analysis Workflow ◽  
A Cell

Abstract Summary DNA methylation patterns in a cell are associated with gene expression and the phenotype of a cell, including disease states. Bisulphite PCR sequencing is commonly used to assess the methylation profile of genomic regions between different cells. Here we have developed MethPanel, a computational pipeline with an interactive graphical interface to rapidly analyse multiplex bisulphite PCR sequencing data. MethPanel comprises a complete analysis workflow from genomic alignment to DNA methylation calling and supports an unlimited number of PCR amplicons and input samples. MethPanel offers important and unique features, such as calculation of a epipolymorphism score and bisulphite PCR bias correction capabilities, and is designed so that the methylation data from all samples can be processed in parallel. The outputs are automatically forwarded to a shinyApp for convenient display, visualisation and remotely sharing data with collaborators and clinicians. Availability MethPanel is freely available at https://github.com/thinhong/MethPanel. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals GPU Accelerated Adaptive Banded Event Alignment for Rapid Comparative Nanopore Signal Analysis

2019 ◽  
Author(s):  
Hasindu Gamaarachchi ◽  
Chun Wai Lam ◽  
Gihan Jayatilaka ◽  
Hiruna Samarakoon ◽  
Jared T. Simpson ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Embedded System ◽  
High Performance ◽  
Point Of Care ◽  
Dynamic Programming Algorithm ◽  
Reference Sequence ◽  
Programming Algorithm ◽  
Sequencing Data ◽  
On Chip ◽  
Gpu Architectures

AbstractNanopore sequencing has the potential to revolutionise genomics by realising portable, real-time sequencing applications, including point-of-care diagnostics and in-the-field genotyping. Achieving these applications requires efficient bioinformatic algorithms for the analysis of raw nanopore signal data. For instance, comparing raw nanopore signals to a biological reference sequence is a computationally complex task despite leveraging a dynamic programming algorithm for Adaptive Banded Event Alignment (ABEA)—a commonly used approach to polish sequencing data and identify non-standard nucleotides, such as measuring DNA methylation. Here, we parallelise and optimise an implementation of the ABEA algorithm (termed f5c) to efficiently run on heterogeneous CPU-GPU architectures. By optimising memory, compute and load balancing between CPU and GPU, we demonstrate how f5c can perform ~3-5× faster than the original implementation of ABEA in the Nanopolish software package. We also show that f5c enables DNA methylation detection on-the-fly using an embedded System on Chip (SoC) equipped with GPUs. Our work not only demonstrates that complex genomics analyses can be performed on lightweight computing systems, but also benefits High-Performance Computing (HPC). The associated source code for f5c along with GPU optimised ABEA is available at https://github.com/hasindu2008/f5c.

scholarly journals High-performance magneto-rheological clutches for direct-drive actuation: Design and development

2021 ◽  
pp. 1045389X2110069
Author(s):  
Sergey Pisetskiy ◽  
Mehrdad Kermani
Keyword(s):  
High Performance ◽  
Degrees Of Freedom ◽  
Dynamic Range ◽  
Complete Analysis ◽  
Mass Ratio ◽  
Direct Drive ◽  
Element Analysis ◽  
Prototype Development ◽  
Magneto Rheological ◽  
Hall Sensors

This paper presents an improved design, complete analysis, and prototype development of high torque-to-mass ratio Magneto-Rheological (MR) clutches. The proposed MR clutches are intended as the main actuation mechanism of a robotic manipulator with five degrees of freedom. Multiple steps to increase the toque-to-mass ratio of the clutch are evaluated and implemented in one design. First, we focus on the Hall sensors’ configuration. Our proposed MR clutches feature embedded Hall sensors for the indirect torque measurement. A new arrangement of the sensors with no effect on the magnetic reluctance of the clutch is presented. Second, we improve the magnetization of the MR clutch. We utilize a new hybrid design that features a combination of an electromagnetic coil and a permanent magnet for improved torque-to-mass ratio. Third, the gap size reduction in the hybrid MR clutch is introduced and the effect of such reduction on maximum torque and the dynamic range of MR clutch is investigated. Finally, the design for a pair of MR clutches with a shared magnetic core for antagonistic actuation of the robot joint is presented and experimentally validated. The details of each approach are discussed and the results of the finite element analysis are used to highlight the required engineering steps and to demonstrate the improvements achieved. Using the proposed design, several prototypes of the MR clutch with various torque capacities ranging from 15 to 200 N·m are developed, assembled, and tested. The experimental results demonstrate the performance of the proposed design and validate the accuracy of the analysis used for the development.

scholarly journals PATH-11. PROSPECTIVE (EPI-)GENETIC CLASSIFICATION OF > 1,000 PEDIATRIC CNS TUMORS—THE MNP 2.0 STUDY

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii426-iii426
Author(s):  
Dominik Sturm ◽  
Felix Sahm ◽  
Felipe Andreiuolo ◽  
David Capper ◽  
Marco Gessi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Gene Panel ◽  
Cns Tumors ◽  
Lower Grade ◽  
High Grade ◽  
Sequencing Data ◽  
Cns Tumor ◽  
Gene Panel Sequencing ◽  
Tumor Entities ◽  
Panel Sequencing

Abstract The large variety of CNS tumor entities affecting children and adolescents, some of which are exceedingly rare, results in very diverging patient outcomes and renders accurate diagnosis challenging. To assess the diagnostic utility of routine DNA methylation-based CNS tumor classification and gene panel sequencing, the Molecular Neuropathology 2.0 study prospectively integrated these (epi-)genetic analyses with reference neuropathological diagnostics as an international trial for newly-diagnosed pediatric patients. In a four-year period, 1,215 patients with sufficient tissue were enrolled from 65 centers, receiving a reference neuropathological diagnosis according to the WHO classification in >97%. Using 10 FFPE sections as input, DNA methylation analysis was successfully performed in 95% of cases, of which 78% with sufficient tumor cell content were assigned to a distinct epigenetic tumor class. The remaining 22% did not match any of 82 represented classes, indicating novel rare tumor entities. Targeted gene panel sequencing of >130 genes performed for 96% of patients with matched blood samples detected diagnostically, prognostically, or therapeutically relevant somatic alterations in 48%. Germline DNA sequencing data indicated potential predisposition syndromes in ~10% of patients. Discrepant results by neuropathological and epigenetic classification (29%) were enriched in histological high-grade gliomas and implicated clinical relevance in 5% of all cases. Clinical follow-up suggests improved survival for some patients with high-grade glioma histology and lower-grade molecular profiles. Routine (epi-)genetic profiling at the time of primary diagnosis adds a valuable layer of information to neuropathological diagnostics and will improve clinical management of CNS tumors.

scholarly journals deepBase v3.0: expression atlas and interactive analysis of ncRNAs from thousands of deep-sequencing data

2020 ◽  
Vol 49 (D1) ◽  
pp. D877-D883
Author(s):  
Fangzhou Xie ◽  
Shurong Liu ◽  
Junhao Wang ◽  
Jiajia Xuan ◽  
Xiaoqin Zhang ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Clinical Information ◽  
Sequencing Data ◽  
Normal Tissues ◽  
Interactive Analysis ◽  
High Throughput Sequencing Data ◽  
Expression Atlas ◽  
Expression Evolution ◽  
Noninvasive Biomarkers ◽  
Cancer Tissues

Abstract Eukaryotic genomes encode thousands of small and large non-coding RNAs (ncRNAs). However, the expression, functions and evolution of these ncRNAs are still largely unknown. In this study, we have updated deepBase to version 3.0 (deepBase v3.0, http://rna.sysu.edu.cn/deepbase3/index.html), an increasingly popular and openly licensed resource that facilitates integrative and interactive display and analysis of the expression, evolution, and functions of various ncRNAs by deeply mining thousands of high-throughput sequencing data from tissue, tumor and exosome samples. We updated deepBase v3.0 to provide the most comprehensive expression atlas of small RNAs and lncRNAs by integrating ∼67 620 data from 80 normal tissues and ∼50 cancer tissues. The extracellular patterns of various ncRNAs were profiled to explore their applications for discovery of noninvasive biomarkers. Moreover, we constructed survival maps of tRNA-derived RNA Fragments (tRFs), miRNAs, snoRNAs and lncRNAs by analyzing >45 000 cancer sample data and corresponding clinical information. We also developed interactive webs to analyze the differential expression and biological functions of various ncRNAs in ∼50 types of cancers. This update is expected to provide a variety of new modules and graphic visualizations to facilitate analyses and explorations of the functions and mechanisms of various types of ncRNAs.

scholarly journals A new parallel pipeline for DNA methylation analysis of long reads datasets

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Ricardo Olanda ◽  
Mariano Pérez ◽  
Juan M. Orduña ◽  
Joaquín Tárraga ◽  
Joaquín Dopazo
Keyword(s):  
Dna Methylation ◽  
Methylation Analysis ◽  
Parallel Pipeline ◽  
Long Reads ◽  
Dna Methylation Analysis

Abstract MP42: Adherence To Healthy Dietary Patterns In Pregnancy And Placental Dna Methylation- An Epigenome Wide Association Study

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Cuilin Zhang ◽  
Jing Wu ◽  
Marion Ouidir ◽  
Stefanie Hinkle ◽  
Fasil Ayele
Keyword(s):  
Dna Methylation ◽  
Dietary Patterns ◽  
First Trimester ◽  
Healthy Eating Index ◽  
Nervous System Development ◽  
Dietary Quality ◽  
Analysis Tool ◽  
Linear Regression Models ◽  
Cpg Sites ◽  
In Pregnancy

Background: Accumulating evidence support the intergenerational impacts of diet in pregnancy. The underlying mechanisms, however, remain unclear. Placental epigenetic mechanisms may be involved although data from human epidemiological studies are sparse. We aimed to investigate associations of dietary quality in pregnancy with epigenome-wide placental DNA methylation in a multiracial pregnancy cohort. Methods: DNA methylation was measured using the Illumina Infinium Human Methylation450 Beadchip on placentas obtained at delivery from 301 pregnant women who participated in the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort. Dietary information during periconception and early first trimester was collected using food frequency questionnaires, and diet in the second and third trimester was collected using a 24-hour dietary recall during four study visits. Scores for adherence to three healthy dietary patterns, alternate Healthy Eating Index (aHEI), alternate Mediterranean Diet (aMED), and Dietary Approaches to Stop Hypertension (DASH), were calculated. For associations of each dietary pattern score with methylation, we conducted analyses using robust linear regression models after the adjustment for age, pre-pregnancy body mass index, race/ethnicity, physical activity, total energy intakes, and population stratification. Genes annotating the top significant CpG sites (false discovery rate (FDR) adjusted P<0.05) were queried for enrichment of functional pathways using the Ingenuity Pathway Analysis tool. Results: Adherence to aHEI was significantly associated with methylation of 8 CpG sites, with the most significant association manifested in cg16724319- MDH1B (P=1.9x10 -10 ). Adherence to aMED was related to methylation of 14 CpG sites, with the most significant association manifested in cg07835181- CLCN7 (P=1.7x10 -11 ). DASH was significantly related to 33 CpG sites, with the most significant association manifested in cg26292547- REV3L (P=4.4x10 -10 ). Further, genes annotating the significant CpG sites were enriched in pathways related to cardiovascular and nervous system development and function, cancer, organismal injury and abnormalities, and reproductive system diseases. Conclusion: Findings from the epigenome wide study suggest that overall dietary quality in pregnancy is associated with placental DNA methylation changes at different loci potentially related to cardiovascular, neurological, reproductive, and cancer phenotypes.

scholarly journals BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach

2014 ◽  
Vol 15 (2) ◽  
pp. R35 ◽  
Author(s):  
Andrea Riebler ◽  
Mirco Menigatti ◽  
Jenny Z Song ◽  
Aaron L Statham ◽  
Clare Stirzaker ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bayesian Approach ◽  
Sequencing Data ◽  
Affinity Capture ◽  
Capture Sequencing

scholarly journals Investigating Pathogenic and Hepatocarcinogenic Mechanisms from Normal Liver to HCC by Constructing Genetic and Epigenetic Networks via Big Genetic and Epigenetic Data Mining and Genome-Wide NGS Data Identification

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Cheng-Wei Li ◽  
Yu-Kai Chiu ◽  
Bor-Sen Chen
Keyword(s):  
Data Mining ◽  
Dna Methylation ◽  
Normal Liver ◽  
Liver Cells ◽  
Next Generation Sequencing Data ◽  
Valuable Insight ◽  
Biliary Cirrhosis ◽  
Sequencing Data ◽  
Cellular Mechanisms ◽  
Genome Wide

The prevalence of hepatocellular carcinoma (HCC) is still high worldwide because liver diseases could develop into HCC. Recent reports indicate nonalcoholic fatty liver disease and nonalcoholic steatohepatitis (NAFLD&NASH) and primary biliary cirrhosis and primary sclerosing cholangitis (PBC&PSC) are significant of HCC. Therefore, understanding the cellular mechanisms of the pathogenesis and hepatocarcinogenesis from normal liver cells to HCC through NAFLD&NASH or PBC&PSC is a priority to prevent the progression of liver damage and reduce the risk of further complications. By the genetic and epigenetic data mining and the system identification through next-generation sequencing data and its corresponding DNA methylation profiles of liver cells in normal, NAFLD&NASH, PBC&PSC, and HCC patients, we identified the genome-wide real genetic and epigenetic networks (GENs) of normal, NAFLD&NASH, PBC&PSC, and HCC patients. In order to get valuable insight into these identified genome-wide GENs, we then applied a principal network projection method to extract the corresponding core GENs for normal liver cells, NAFLD&NASH, PBC&PSC, and HCC. By comparing the signal transduction pathways involved in the identified core GENs, we found that the hepatocarcinogenesis through NAFLD&NASH was induced through DNA methylation of HIST2H2BE, HSPB1, RPL30, and ALDOB and the regulation of miR-21 and miR-122, and the hepatocarcinogenesis through PBC&PSC was induced through DNA methylation of RPL23A, HIST2H2BE, TIMP1, IGF2, RPL30, and ALDOB and the regulation of miR-29a, miR-21, and miR-122. The genetic and epigenetic changes in the pathogenesis and hepatocarcinogenesis potentially serve as potential diagnostic biomarkers and/or therapeutic targets.

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