scholarly journals ClinGen Variant Curation Interface: A Variant Classification Platform for the Application of Evidence Criteria from ACMG/AMP Guidelines

2021 ◽  
Author(s):  
Christine G. Preston ◽  
Matt W. Wright ◽  
Rao Madhavrao ◽  
Steven M. Harrison ◽  
Jennifer L. Goldstein ◽  
...  
Keyword(s):  
Genetic Alterations ◽  
Healthcare Management ◽  
Evidence Based ◽  
Variant Classification ◽  
Sequencing Technologies ◽  
Relevant Evidence ◽  
Central Platform ◽  
Clinically Significant ◽  
Generation Sequencing

AbstractBackgroundIdentification of clinically significant genetic alterations involved in human disease has been dramatically accelerated by developments in next-generation sequencing technologies. However, the infrastructure and accessible comprehensive curation tools necessary for analyzing an individual patient genome and interpreting genetic variants to inform healthcare management have been lacking.ResultsHere we present the ClinGen Variant Curation Interface (VCI), a global open-source variant classification platform for supporting the application of evidence criteria and classification of variants based on the ACMG/AMP variant classification guidelines. The VCI is among a suite of tools developed by the NIH-funded Clinical Genome Resource (ClinGen) Consortium, and supports an FDA-recognized human variant curation process. Essential to this is the ability to enable collaboration and peer review across ClinGen Expert Panels supporting users in comprehensively identifying, annotating, and sharing relevant evidence while making variant pathogenicity assertions. To facilitate evidence-based improvements in human variant classification, the VCI is publicly available to the genomics community and is available at https://curation.clinicalgenome.org. Navigation workflows support users providing guidance to comprehensively apply the ACMG/AMP evidence criteria and document provenance for asserting variant classifications.ConclusionThe VCI offers a central platform for clinical variant classification that fills a gap in the learning healthcare system, and facilitates widespread adoption of standards for clinical curation.

scholarly journals Application of BERT to Enable Gene Classification Based on Clinical Evidence

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuhan Su ◽  
Hongxin Xiang ◽  
Haotian Xie ◽  
Yong Yu ◽  
Shiyan Dong ◽  
...  
Keyword(s):  
Clinical Evidence ◽  
Genetic Mutations ◽  
Data Presentation ◽  
Sequencing Technologies ◽  
Practical Tool ◽  
Logarithmic Loss ◽  
Manual Classification ◽  
High Repeatability ◽  
Generation Sequencing

The identification of profiled cancer-related genes plays an essential role in cancer diagnosis and treatment. Based on literature research, the classification of genetic mutations continues to be done manually nowadays. Manual classification of genetic mutations is pathologist-dependent, subjective, and time-consuming. To improve the accuracy of clinical interpretation, scientists have proposed computational-based approaches for automatic analysis of mutations with the advent of next-generation sequencing technologies. Nevertheless, some challenges, such as multiple classifications, the complexity of texts, redundant descriptions, and inconsistent interpretation, have limited the development of algorithms. To overcome these difficulties, we have adapted a deep learning method named Bidirectional Encoder Representations from Transformers (BERT) to classify genetic mutations based on text evidence from an annotated database. During the training, three challenging features such as the extreme length of texts, biased data presentation, and high repeatability were addressed. Finally, the BERT+abstract demonstrates satisfactory results with 0.80 logarithmic loss, 0.6837 recall, and 0.705 F -measure. It is feasible for BERT to classify the genomic mutation text within literature-based datasets. Consequently, BERT is a practical tool for facilitating and significantly speeding up cancer research towards tumor progression, diagnosis, and the design of more precise and effective treatments.

scholarly journals HD Spot: Interpretable Deep Learning Classification of Single Cell Transcript Data

2019 ◽  
Author(s):  
Eric Prince ◽  
Todd C. Hankinson
Keyword(s):  
Deep Learning ◽  
Single Cell ◽  
High Throughput ◽  
Ground Truth ◽  
Sequencing Technologies ◽  
Bioinformatic Tool ◽  
Complex Relationships ◽  
Insight Into ◽  
Generation Sequencing

ABSTRACTHigh throughput data is commonplace in biomedical research as seen with technologies such as single-cell RNA sequencing (scRNA-seq) and other Next Generation Sequencing technologies. As these techniques continue to be increasingly utilized it is critical to have analysis tools that can identify meaningful complex relationships between variables (i.e., in the case of scRNA-seq: genes) in a way such that human bias is absent. Moreover, it is equally paramount that both linear and non-linear (i.e., one-to-many) variable relationships be considered when contrasting datasets. HD Spot is a deep learning-based framework that generates an optimal interpretable classifier a given high-throughput dataset using a simple genetic algorithm as well as an autoencoder to classifier transfer learning approach. Using four unique publicly available scRNA-seq datasets with published ground truth, we demonstrate the robustness of HD Spot and the ability to identify ontologically accurate gene lists for a given data subset. HD Spot serves as a bioinformatic tool to allow novice and advanced analysts to gain complex insight into their respective datasets enabling novel hypotheses development.

scholarly journals Advances in genetics: widening our understanding of prostate cancer

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1512 ◽  
Author(s):  
Angela C. Pine ◽  
Flavia F. Fioretti ◽  
Greg N. Brooke ◽  
Charlotte L. Bevan
Keyword(s):  
Prostate Cancer ◽  
Exome Sequencing ◽  
Personalised Medicine ◽  
Therapy Response ◽  
Genetic Alterations ◽  
Sequencing Technologies ◽  
Whole Exome ◽  
Disease Predisposition ◽  
Generation Sequencing ◽  
Made In

Prostate cancer is a leading cause of cancer-related death in Western men. Our understanding of the genetic alterations associated with disease predisposition, development, progression, and therapy response is rapidly improving, at least in part, owing to the development of next-generation sequencing technologies. Large advances have been made in our understanding of the genetics of prostate cancer through the application of whole-exome sequencing, and this review summarises recent advances in this field and discusses how exome sequencing could be used clinically to promote personalised medicine for prostate cancer patients.

scholarly journals Advances in understanding the molecular pathology of gynecological malignancies: the role and potential of RNA sequencing

2021 ◽  
pp. ijgc-2021-002509
Author(s):  
Alba Southern ◽  
Mona El-Bahrawy
Keyword(s):  
Rna Sequencing ◽  
Molecular Pathology ◽  
Transcript Abundance ◽  
Genetic Alterations ◽  
Gynecological Cancers ◽  
The Past ◽  
Sequencing Technologies ◽  
Technological Limitations ◽  
Generation Sequencing

For many years technological limitations restricted the progress of identifying the underlying genetic causes of gynecologicalcancers. However, during the past decade, high-throughput next-generation sequencing technologies have revolutionized cancer research. RNA sequencing has arisen as a very useful technique in expanding our understanding of genome changes in cancer. Cancer is characterized by the accumulation of genetic alterations affecting genes, including substitutions, insertions, deletions, translocations, gene fusions, and alternative splicing. If these aberrant genes become transcribed, aberrations can be detected by RNA sequencing, which will also provide information on the transcript abundance revealing the expression levels of the aberrant genes. RNA sequencing is considered the technique of choice when studying gene expression and identifying new RNA species. This is due to the quantitative and qualitative improvement that it has brought to transcriptome analysis, offering a resolution that allows research into different layers of transcriptome complexity. It has also been successful in identifying biomarkers, fusion genes, tumor suppressors, and uncovering new targets responsible for drug resistance in gynecological cancers. To illustrate that we here review the role of RNA sequencing in studies that enhanced our understanding of the molecular pathology of gynecological cancers.

The death of Sergey Esenin: A forensic’s view of the cultural and historical event

2018 ◽  
pp. 153-165
Author(s):  
L. V. Bertovsky ◽  
V. M. Klyueva ◽  
A. L. Lisovetsky
Keyword(s):  
Interdisciplinary Approach ◽  
Historical Event ◽  
Russian Culture ◽  
Know How ◽  
Relevant Evidence ◽  
History Of

Sergey Esenin’s tragic end is widely known and provokes disputes to this day. The official reports put it down as a suicide. The incident could be analyzed more effectively by means of an interdisciplinary approach using the latest forensic know-how. The documented circumstances of Esenin’s death, found in recorded testimonies and interviews, as well as the materials of the Russian National Esenin Committee of Writers, are examined through the author’s own classification of forensically relevant evidence of suicide. The analysis reveals that suicide remains the most probable version. Far from solving this incident for good, these conclusions may become an important forensic contribution to the history of Russian culture.

The Influence of Memory-Aware Computation on Distributed BLAST

2019 ◽  
Vol 14 (2) ◽  
pp. 157-163
Author(s):  
Majid Hajibaba ◽  
Mohsen Sharifi ◽  
Saeid Gorgin
Keyword(s):  
Search Time ◽  
Genomic Research ◽  
Local Alignment ◽  
Negative Effects ◽  
Sequencing Technologies ◽  
Percent Improvement ◽  
Fast Processing ◽  
Search Tool ◽  
Memory Awareness ◽  
Generation Sequencing

Background: One of the pivotal challenges in nowadays genomic research domain is the fast processing of voluminous data such as the ones engendered by high-throughput Next-Generation Sequencing technologies. On the other hand, BLAST (Basic Local Alignment Search Tool), a longestablished and renowned tool in Bioinformatics, has shown to be incredibly slow in this regard. Objective: To improve the performance of BLAST in the processing of voluminous data, we have applied a novel memory-aware technique to BLAST for faster parallel processing of voluminous data. Method: We have used a master-worker model for the processing of voluminous data alongside a memory-aware technique in which the master partitions the whole data in equal chunks, one chunk for each worker, and consequently each worker further splits and formats its allocated data chunk according to the size of its memory. Each worker searches every split data one-by-one through a list of queries. Results: We have chosen a list of queries with different lengths to run insensitive searches in a huge database called UniProtKB/TrEMBL. Our experiments show 20 percent improvement in performance when workers used our proposed memory-aware technique compared to when they were not memory aware. Comparatively, experiments show even higher performance improvement, approximately 50 percent, when we applied our memory-aware technique to mpiBLAST. Conclusion: We have shown that memory-awareness in formatting bulky database, when running BLAST, can improve performance significantly, while preventing unexpected crashes in low-memory environments. Even though distributed computing attempts to mitigate search time by partitioning and distributing database portions, our memory-aware technique alleviates negative effects of page-faults on performance.

What Every Neuropathologist Needs to Know: Practical Aspects and Pitfalls in Molecular Diagnosis of Brain Tumors

2021 ◽  
Author(s):  
J Stephen Nix ◽  
Cristiane M Ida
Keyword(s):  
Brain Tumors ◽  
Molecular Diagnosis ◽  
Genetic Alterations ◽  
Genetic Alteration ◽  
Molecular Testing ◽  
Test Results ◽  
Molecular Test ◽  
Molecular Tests ◽  
Clinically Significant ◽  
Selection Of

Abstract Molecular testing has become part of the routine diagnostic workup of brain tumors after the implementation of integrated histomolecular diagnoses in the 2016 WHO classification update. It is important for every neuropathologist to be aware of practical preanalytical, analytical, and postanalytical factors that impact the performance and interpretation of molecular tests. Prior to testing, optimizing tumor purity and tumor amount increases the ability of the molecular test to detect the genetic alteration of interest. Recognizing basic molecular testing platform analytical characteristics allows selection of the optimal platform for each clinicopathological scenario. Finally, postanalytical considerations to properly interpret molecular test results include understanding the clinical significance of the detected genetic alteration, recognizing that detected clinically significant genetic alterations are occasionally germline constitutional rather than somatic tumor-specific, and being cognizant that recommended and commonly used genetic nomenclature may differ. Potential pitfalls in brain tumor molecular diagnosis are also discussed.

scholarly journals Clinical Implications of Polymicrobial Synergism Effects on Antimicrobial Susceptibility

Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 144
Author(s):  
William Little ◽  
Caroline Black ◽  
Allie Clinton Smith
Keyword(s):  
Antimicrobial Susceptibility ◽  
Chronic Wounds ◽  
Clinical Laboratory ◽  
Patient Treatment ◽  
Clinical Implications ◽  
Clinical Environment ◽  
Tolerance Mechanisms ◽  
Sequencing Technologies ◽  
Generation Sequencing ◽  
Polymicrobial Infections

With the development of next generation sequencing technologies in recent years, it has been demonstrated that many human infectious processes, including chronic wounds, cystic fibrosis, and otitis media, are associated with a polymicrobial burden. Research has also demonstrated that polymicrobial infections tend to be associated with treatment failure and worse patient prognoses. Despite the importance of the polymicrobial nature of many infection states, the current clinical standard for determining antimicrobial susceptibility in the clinical laboratory is exclusively performed on unimicrobial suspensions. There is a growing body of research demonstrating that microorganisms in a polymicrobial environment can synergize their activities associated with a variety of outcomes, including changes to their antimicrobial susceptibility through both resistance and tolerance mechanisms. This review highlights the current body of work describing polymicrobial synergism, both inter- and intra-kingdom, impacting antimicrobial susceptibility. Given the importance of polymicrobial synergism in the clinical environment, a new system of determining antimicrobial susceptibility from polymicrobial infections may significantly impact patient treatment and outcomes.

scholarly journals A Review of Evidence-Based Recommendations for Pericoronitis Management and a Systematic Review of Antibiotic Prescribing for Pericoronitis among Dentists: Inappropriate Pericoronitis Treatment Is a Critical Factor of Antibiotic Overuse in Dentistry

2021 ◽  
Vol 18 (13) ◽  
pp. 6796
Author(s):  
Jan Schmidt ◽  
Martina Kunderova ◽  
Nela Pilbauerova ◽  
Martin Kapitan
Keyword(s):  
Systematic Review ◽  
Local Therapy ◽  
Critical Factor ◽  
Antibiotic Use ◽  
Narrative Review ◽  
Antibiotic Prescribing ◽  
Evidence Based ◽  
Antibiotic Overuse ◽  
Clinically Significant

This work provides a narrative review covering evidence-based recommendations for pericoronitis management (Part A) and a systematic review of antibiotic prescribing for pericoronitis from January 2000 to May 2021 (Part B). Part A presents the most recent, clinically significant, and evidence-based guidance for pericoronitis diagnosis and proper treatment recommending the local therapy over antibiotic prescribing, which should be reserved for severe conditions. The systematic review includes publications analyzing sets of patients treated for pericoronitis and questionnaires that identified dentists' therapeutic approaches to pericoronitis. Questionnaires among dentists revealed that almost 75% of them prescribed antibiotics for pericoronitis, and pericoronitis was among the top 4 in the frequency of antibiotic use within the surveyed diagnoses and situations. Studies involving patients showed that antibiotics were prescribed to more than half of the patients with pericoronitis, and pericoronitis was among the top 2 in the frequency of antibiotic use within the monitored diagnoses and situations. The most prescribed antibiotics for pericoronitis were amoxicillin and metronidazole. The systematic review results show abundant and unnecessary use of antibiotics for pericoronitis and are in strong contrast to evidence-based recommendations summarized in the narrative review. Adherence of dental professionals to the recommendations presented in this work can help rapidly reduce the duration of pericoronitis, prevent its complications, and reduce the use of antibiotics and thus reduce its impact on patients' quality of life, healthcare costs, and antimicrobial resistance development.

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