scholarly journals SOFTWARE ANALYSIS OF STRUCTURE BLOCK-CYCLIC BASIC MATRIX OF DCT

2020 ◽  
Vol 0 (3) ◽  
pp. 173-180
Author(s):  
I. O. Protsko ◽  
M. V. Mishchuk
Keyword(s):  
Basic Matrix ◽  
Software Analysis

Elements of the Basic Matrix for Integrating Marital and Family Therapy

1990 ◽  
Vol 35 (3) ◽  
pp. 280-281
Author(s):  
Cas Schaap ◽  
Kees Hoogduin
Keyword(s):  
Family Therapy ◽  
Marital And Family Therapy ◽  
Basic Matrix

A Time-Resolved Low-Angle Light Scattering Apparatus. Application to Phase Separation Problems in Polymer Systems

2001 ◽  
Vol 66 (6) ◽  
pp. 973-982 ◽  
Author(s):  
Čestmír Koňák ◽  
Jaroslav Holoubek ◽  
Petr Štěpánek
Keyword(s):  
Phase Separation ◽  
Light Scattering ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Ccd Camera ◽  
Time Resolved ◽  
Polymer Systems ◽  
Software Analysis ◽  
Phase Separation Kinetics ◽  
Small Angle Light Scattering

A time-resolved small-angle light scattering apparatus equipped with azimuthal integration by means of a conical lens or software analysis of scattering patterns detected with a CCD camera was developed. Averaging allows a significant reduction of the signal-to-noise ratio of scattered light and makes this technique suitable for investigation of phase separation kinetics. Examples of applications to time evolution of phase separation in concentrated statistical copolymer solutions and dissolution of phase-separated domains in polymer blends are given.

scholarly journals 423. SARS-CoV-2 NGS Assay Powered by Biotia COVID-DX Software

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S278-S279
Author(s):  
Dorottya Nagy-Szakal ◽  
Mara Couto-Rodriguez ◽  
Joseph Barrows ◽  
Heather L Wells ◽  
Marilyne Debieu ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Viral Genome ◽  
Board Member ◽  
Limit Of Detection ◽  
Clinical Samples ◽  
Analysis Tool ◽  
Viral Titer ◽  
Target Enrichment ◽  
Library Preparation ◽  
Software Analysis

Abstract Background COVID-19 had spread quickly, causing an international public health emergency with an alarming global shortage of COVID-19 diagnostic tests. We developed and clinically validated a next-generation sequencing (NGS)-based target enrichment assay with the COVID-DX Software tailored for the detection, characterization, and surveillance of the SARS-CoV-2 viral genome. Methods The SARS-CoV-2 NGS assay consists of components including library preparation, target enrichment, sequencing, and a COVID-DX Software analysis tool. The NGS library preparation starts with extracted RNA from nasopharyngeal (NP) swabs followed by cDNA synthesis and conversion to Illumina TruSeq-compatible libraries using the Twist Library Preparation Kit via Enzymatic Fragmentation and Unique Dual Indices (UDI). The library is then enriched for SARS-CoV-2 sequences using a panel of dsDNA biotin-labeled probes, specifically designed to target the SARS-CoV-2 genome, then sequenced on an Illumina NextSeq 550 platform. The COVID-DX Software analyzes sequence results and provides a clinically oriented report, including the presence/absence of SARS-CoV-2 for diagnostic use. An additional research use only report describes the assay performance, estimated viral titer, coverage across the viral genome, genetic variants, and phylogenetic analysis. Results The SARS-CoV-2 NGS Assay was validated on 30 positive and 30 negative clinical samples. To measure the sensitivity and specificity of the assay, the positive and negative percent agreement (PPA, NPA) was defined in comparison to an orthogonal EUA RT-PCR assay (PPA [95% CI]: 96.77% [90.56%-100%] and NPA [95% CI]: 100% [100%-100%]). Data reported using our assay defined the limit of detection to be 40 copies/ml using heat-inactivated SARS-CoV-2 viral genome in clinical matrices. In-silico analysis provided >99.9% coverage across the SARS-CoV-2 viral genome and no cross-reactivity with evolutionarily similar respiratory pathogens. Conclusion The SARS-CoV-2 NGS Assay powered by the COVID-DX Software can be used to detect the SARS-CoV-2 virus and provide additional insight into viral titer and genetic variants to track transmission, stratify risk, predict outcome and therapeutic response, and control the spread of infectious disease. Disclosures Dorottya Nagy-Szakal, MD PhD, Biotia (Employee) Mara Couto-Rodriguez, MS, Biotia (Employee) Joseph Barrows, MS, Biotia, Inc. (Employee, Shareholder) Heather L. Wells, MPH, Biotia (Consultant) Marilyne Debieu, PhD, Biotia (Employee) Courteny Hager, BS, Biotia (Employee) Kristin Butcher, MS, Twist Bioscience (Employee) Siyuan Chen, PhD, Twist Bioscience (Employee) Christopher Mason, PhD, Biotia (Board Member, Employee, Shareholder) Niamh B. O’Hara, PhD, Biotia (Board Member, Employee, Shareholder)Twist (Other Financial or Material Support, I am CEO of Biotia and Biotia has business partnership with Twist)

scholarly journals NGS-based identification and tracing of microsatellite instability from minute amounts DNA using inter-Alu-PCR

2020 ◽  
Author(s):  
Fangyan Yu ◽  
Ka Wai Leong ◽  
Alexander Makrigiorgos ◽  
Viktor A Adalsteinsson ◽  
Ioannis Ladas ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Analysis Tool ◽  
Circulating Dna ◽  
Liquid Biopsies ◽  
Software Analysis ◽  
Multiplexed Pcr ◽  
Human Genomes ◽  
Custom Made ◽  
Alu Element ◽  
Next Generation Sequencing Ngs

Abstract Sensitive detection of microsatellite instability (MSI) in tissue or liquid biopsies using next generation sequencing (NGS) has growing prognostic and predictive applications in cancer. However, the complexities of NGS make it cumbersome as compared to established multiplex-PCR detection of MSI. We present a new approach to detect MSI using inter-Alu-PCR followed by targeted NGS, that combines the practical advantages of multiplexed-PCR with the breadth of information provided by NGS. Inter-Alu-PCR employs poly-adenine repeats of variable length present in every Alu element and provides a massively-parallel, rapid approach to capture poly-A-rich genomic fractions within short 80–150bp amplicons generated from adjacent Alu-sequences. A custom-made software analysis tool, MSI-tracer, enables Alu-associated MSI detection from tissue biopsies or MSI-tracing at low-levels in circulating-DNA. MSI-associated indels at somatic-indel frequencies of 0.05–1.5% can be detected depending on the availability of matching normal tissue and the extent of instability. Due to the high Alu copy-number in human genomes, a single inter-Alu-PCR retrieves enough information for identification of MSI-associated-indels from ∼100 pg circulating-DNA, reducing current limits by ∼2-orders of magnitude and equivalent to circulating-DNA obtained from finger-sticks. The combined practical and informational advantages of inter-Alu-PCR make it a powerful tool for identifying tissue-MSI-status or tracing MSI-associated-indels in liquid biopsies.

scholarly journals Searching for improvements in predicting human eye colour from DNA

2021 ◽  
Author(s):  
Magdalena Kukla-Bartoszek ◽  
Paweł Teisseyre ◽  
Ewelina Pośpiech ◽  
Joanna Karłowska-Pik ◽  
Piotr Zieliński ◽  
...  
Keyword(s):  
Machine Learning ◽  
Regression Models ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Sequencing Analysis ◽  
Learning Approaches ◽  
Human Eye ◽  
Software Analysis ◽  
Whole Exome ◽  
Eye Colour

AbstractIncreasing understanding of human genome variability allows for better use of the predictive potential of DNA. An obvious direct application is the prediction of the physical phenotypes. Significant success has been achieved, especially in predicting pigmentation characteristics, but the inference of some phenotypes is still challenging. In search of further improvements in predicting human eye colour, we conducted whole-exome (enriched in regulome) sequencing of 150 Polish samples to discover new markers. For this, we adopted quantitative characterization of eye colour phenotypes using high-resolution photographic images of the iris in combination with DIAT software analysis. An independent set of 849 samples was used for subsequent predictive modelling. Newly identified candidates and 114 additional literature-based selected SNPs, previously associated with pigmentation, and advanced machine learning algorithms were used. Whole-exome sequencing analysis found 27 previously unreported candidate SNP markers for eye colour. The highest overall prediction accuracies were achieved with LASSO-regularized and BIC-based selected regression models. A new candidate variant, rs2253104, located in the ARFIP2 gene and identified with the HyperLasso method, revealed predictive potential and was included in the best-performing regression models. Advanced machine learning approaches showed a significant increase in sensitivity of intermediate eye colour prediction (up to 39%) compared to 0% obtained for the original IrisPlex model. We identified a new potential predictor of eye colour and evaluated several widely used advanced machine learning algorithms in predictive analysis of this trait. Our results provide useful hints for developing future predictive models for eye colour in forensic and anthropological studies.

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