ClinVar: improvements to accessing data Landrum, Melissa J; Chitipiralla, Shanmuga; Brown, Garth R ...
Nucleic acids research,
01/2020, Letnik:
48, Številka:
D1
Journal Article
Recenzirano
Odprti dostop
Abstract
ClinVar is a freely available, public archive of human genetic variants and interpretations of their relationships to diseases and other conditions, maintained at the National Institutes of ...Health (NIH). Submitted interpretations of variants are aggregated and made available on the ClinVar website (https://www.ncbi.nlm.nih.gov/clinvar/), and as downloadable files via FTP and through programmatic tools such as NCBI’s E-utilities. The default view on the ClinVar website, the Variation page, was recently redesigned. The new layout includes several new sections that make it easier to find submitted data as well as summary data such as all diseases and citations reported for the variant. The new design also better represents more complex data such as haplotypes and genotypes, as well as variants that are in ClinVar as part of a haplotype or genotype but have no interpretation for the single variant. ClinVar's variant-centric XML had its production release in April 2019. The ClinVar website and E-utilities both have been updated to support the VCV (variation in ClinVar) accession numbers found in the variant-centric XML file. ClinVar's search engine has been fine-tuned for improved retrieval of search results.
Abstract
ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the ...National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.
Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and ...Drug Administration (FDA) for another indication is a more rapid and less expensive option. We present DRIAD (Drug Repurposing In AD), a machine learning framework that quantifies potential associations between the pathology of AD severity (the Braak stage) and molecular mechanisms as encoded in lists of gene names. DRIAD is applied to lists of genes arising from perturbations in differentiated human neural cell cultures by 80 FDA-approved and clinically tested drugs, producing a ranked list of possible repurposing candidates. Top-scoring drugs are inspected for common trends among their targets. We propose that the DRIAD method can be used to nominate drugs that, after additional validation and identification of relevant pharmacodynamic biomarker(s), could be readily evaluated in a clinical trial.
We present the discovery of a transiting hot Jupiter orbiting HIP 67522 (Teff ∼ 5650 K; M* ∼ 1.2M ) in the 10-20 Myr old Sco-Cen OB association. We identified the transits in the TESS data using our ...custom notch filter planet search pipeline and characterize the system with additional photometry from Spitzer; spectroscopy from SOAR/Goodman, SALT/HRS, LCOGT/NRES, and SMARTS/CHIRON; and speckle imaging from SOAR/HRCam. We model the photometry as a periodic Gaussian process with transits to account for stellar variability and find an orbital period of days and radius of R⊕. We also identify a single transit of an additional candidate planet with radius R⊕ that has an orbital period of 23 days. The validated planet HIP 67522b is currently the youngest transiting hot Jupiter discovered and is an ideal candidate for transmission spectroscopy and radial velocity follow-up studies, while also demonstrating that some young giant planets either form in situ at small orbital radii or else migrate promptly from formation sites farther out in the disk.
Abstract
Background
The application of machine learning to cardiac auscultation has the potential to improve the accuracy and efficiency of both routine and point-of-care screenings. The use of ...convolutional neural networks (CNN) on heart sound spectrograms in particular has defined state-of-the-art performance. However, the relative paucity of patient data remains a significant barrier to creating models that can adapt to a wide range of potential variability. To that end, we examined a CNN model’s performance on automated heart sound classification, before and after various forms of data augmentation, and aimed to identify the most optimal augmentation methods for cardiac spectrogram analysis.
Results
We built a standard CNN model to classify cardiac sound recordings as either normal or abnormal. The baseline control model achieved a PR AUC of 0.763 ± 0.047. Among the single data augmentation techniques explored, horizontal flipping of the spectrogram image improved the model performance the most, with a PR AUC of 0.819 ± 0.044. Principal component analysis color augmentation (PCA) and perturbations of saturation-value (SV) of the hue-saturation-value (HSV) color scale achieved a PR AUC of 0.779 ± 045 and 0.784 ± 0.037, respectively. Time and frequency masking resulted in a PR AUC of 0.772 ± 0.050. Pitch shifting, time stretching and compressing, noise injection, vertical flipping, and applying random color filters negatively impacted model performance. Concatenating the best performing data augmentation technique (horizontal flip) with PCA and SV perturbations improved model performance.
Conclusion
Data augmentation can improve classification accuracy by expanding and diversifying the dataset, which protects against overfitting to random variance. However, data augmentation is necessarily domain specific. For example, methods like noise injection have found success in other areas of automated sound classification, but in the context of cardiac sound analysis, noise injection can mimic the presence of murmurs and worsen model performance. Thus, care should be taken to ensure clinically appropriate forms of data augmentation to avoid negatively impacting model performance.
We report the photometry of six transits of the hot Jupiter HAT-P-29b obtained from 2013 October to 2015 January. We analyze the new light curves, in combination with the published photometric, ...Doppler velocimetric, and spectroscopic measurements, finding an updated orbital ephemeris for the HAT-P-29 system, and P = 5.723390(13) days. This result is 17.63 s (4.0 ) longer than the previously published value, amounting to errors exceeding 2.5 hr at the time of writing (on UTC 2018 June 1). The measured transit mid-times for HAT-P-29b show no compelling evidence of timing anomalies from a linear model, which rules out the presence of perturbers with masses greater than 0.6, 0.7, 0.5, and 0.4 M⊕ near the 1:2, 2:3, 3:2, and 2:1 resonances with HAT-P-29b, respectively.
Much has changed in the last two years at DGVa (http://www.ebi.ac.uk/dgva) and dbVar (http://www.ncbi.nlm.nih.gov/dbvar). We are now processing direct submissions rather than only curating data from ...the literature and our joint study catalog includes data from over 100 studies in 11 organisms. Studies from human dominate with data from control and case populations, tumor samples as well as three large curated studies derived from multiple sources. During the processing of these data, we have made improvements to our data model, submission process and data representation. Additionally, we have made significant improvements in providing access to these data via web and FTP interfaces.
The purpose of this study was to investigate the experiences of Syrian refugee students in Canadian schools. Article 12 of the Convention on the Rights of the Child (CRC) was used as a framework. ...Data collection involved one-on-one interview with students. Data from the interviews was analyzed using an open-coding technique to identify themes and patterns. Although the students had positive resettlement experiences, some of them experienced difficulties with their learning. Based on the findings, we propose recommendations for educators and schools welcoming Syrian refugee students.
Since 2000, an increasing number of Chinese international students have been entering North American universities, and many have experienced issues with a sense of belonging, which can in turn impact ...their academic, social performance, and psychological wellbeing. However, there is limited research on this topic that is exclusively focused on Chinese international students. Therefore, in order to establish the direction that future research should take, a thorough literature review has been conducted with the aim of exploring those students’ perceptions and experiences regarding sense of belonging, establishing the factors that shape this phenomenon, and identifying the impact it has on students and institutions.
Process-induced inadvertent phase change of an active pharmaceutical ingredient in a drug product could impact chemical stability, physical stability, shelf life, and bioperformance. In this study, ...dispersive Raman spectroscopy is presented as an alternative method for the nondestructive, high-throughput, at-line quantification of amorphous conversion. A quantitative Raman method was developed using a multivariate partial least squares (PLS) regression calibration technique with solid-state nuclear magnetic resonance (ssNMR) spectroscopy as the reference method. Compositionally identical calibration tablets containing 20% w/w total MK-A drug in varying weight proportions (0%-50% w/w based on total MK-A) of amorphous and crystalline MK-A were compressed at 10-45 kN force. PLS predictions of amorphous content of tablets using Raman spectroscopy correlated well with ssNMR quantification. The predictive accuracy of this model led to a strong correlation (R
= 0.987) with a root mean-squared error of prediction of 1.5% w/w amorphous MK-A in tablets up to 50% w/w amorphous conversion in compressive stress range of 60-320 MPa. Overall, these results suggest that dispersive Raman spectroscopy offers fast, sensitive, and high-throughput (<5 min/tablet) method for quantitating amorphous conversion.
PDF
