A Novel Quality-Control Procedure to Improve the Accuracy of Rare Variant Calling in SNP Arrays

Background: Single-nucleotide polymorphism (SNP) arrays are an ideal technology for genotyping genetic variants in mass screening. However, using SNP arrays to detect rare variants [with a minor allele frequency (MAF) of <1%] is still a challenge because of noise signals and batch effects. An approach that improves the genotyping quality is needed for clinical applications.Methods: We developed a quality-control procedure for rare variants which integrates different algorithms, filters, and experiments to increase the accuracy of variant calling. Using data from the TWB 2.0 custom Axiom array, we adopted an advanced normalization adjustment to prevent false calls caused by splitting the cluster and a rare het adjustment which decreases false calls in rare variants. The concordance of allelic frequencies from array data was compared to those from sequencing datasets of Taiwanese. Finally, genotyping results were used to detect familial hypercholesterolemia (FH), thrombophilia (TH), and maturity-onset diabetes of the young (MODY) to assess the performance in disease screening. All heterozygous calls were verified by Sanger sequencing or qPCR. The positive predictive value (PPV) of each step was estimated to evaluate the performance of our procedure.Results: We analyzed SNP array data from 43,433 individuals, which interrogated 267,247 rare variants. The advanced normalization and rare het adjustment methods adjusted genotyping calling of 168,134 variants (96.49%). We further removed 3916 probesets which were discordant in MAFs between the SNP array and sequencing data. The PPV for detecting pathogenic variants with 0.01%<MAF≤1% exceeded 99.37%. PPVs for those with an MAF of ≤0.01% improved from 95% to 100% for FH, 42.11% to 85.19% for TH, and 18.24% to 72.22% for MODY after adopting our rare variant quality-control procedure and experimental verification.Conclusion: Adopting our quality-control procedure, SNP arrays can adequately detect variants with MAF values ranging 0.01%∼0.1%. For variants with MAF values of ≤0.01%, experimental validation is needed unless sequencing data from a homogeneous population of >10,000 are available. The results demonstrated our procedure could perform correct genotype calling of rare variants. It provides a solution of pathogenic variant detection through SNP array. The approach brings tremendous promise for implementing precision medicine in medical practice.

Аnalysis of the technical and dosimetric characteristics of the brachytherapy afterloaders. Ring applicator

A study of the technical and dosimetry characteristics of brachytherapy afterloaders and applicators was carried out. Ring applicator has been taken as an example, the correctness of positioning of a radiation source (RS) inside the applicators was tested as part of the comissioning and quality control procedure of the brachytherapy applicators. The magnitudes of inconsistencies in the position of RS were established when planning and implementing treatment plans for radiation therapy. The identification of the values of the discrepancy was carried out using the obtained X-ray images of the applicator at the time of the implementation of the irradiation plans. The treatment plan was a sequential positioning of RS in the body of the applicator in each active position with a minimum step from the tip to the vaginal part of the applicator. The X-ray image was obtained by locating the source sequentially at each active position of the applicator. When carrying out dosimetric planning, 3 methods of applicator reconstruction were used. The analysis revealed that the applicator reconstruction method affects the magnitude of the discrepancy in determining the position of the source in the lumen of the applicator ring. Using the methods of statistical analysis, the mean, median, maximum and minimum values of the detected deviations were calculated. The results are presented in the form of tables and graphs for all investigated stop positions of IRS. Based on the results of the study, we consider it expedient to carry out quality control procedures when putting applicators into clinical operation. Based on the results obtained, we consider it acceptable to conduct a quality control procedure for the positioning accuracy of radiation sources in the applicators at least 1 time per month. Taking into account the results of the study when carrying out dosimetric planning will improve the quality of the irradiation sessions using the brachytherapy method, thereby improving the quality of oncological care for the population.

Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction

Accurate ship trajectory plays an important role for maritime traffic control and management, and ship trajectory prediction with Automatic Identification System (AIS) data has attracted considerable research attentions in maritime traffic community. The raw AIS data may be contaminated by noises, which limits its usage in maritime traffic management applications in real world. To address the issue, we proposed an ensemble ship trajectory reconstruction framework combining data quality control procedure and prediction module. More specifically, the proposed framework implemented the data quality control procedure in three steps: trajectory separation, data denoising, and normalization. In greater detail, the data quality control procedure firstly identified outliers from the raw ship AIS data sample, which were further cleansed with the moving average model. Then, the denoised data were normalized into evenly distributed data series (in terms of time interval). After that, the proposed framework predicted ship trajectory with the artificial neural network. We verified the proposed model performance with two ship trajectories downloaded from public accessible AIS data base.