scholarly journals Current status and recent advances of next generation sequencing techniques in immunological repertoire

2016 ◽  
Vol 17 (3) ◽  
pp. 153-164 ◽  
Author(s):  
X-L Hou ◽  
L Wang ◽  
Y-L Ding ◽  
Q Xie ◽  
H-Y Diao
Keyword(s):  
Next Generation Sequencing ◽  
Current Status ◽  
Next Generation ◽  
Recent Advances ◽  
Generation Sequencing

scholarly journals The integration of emerging omics approaches to advance precision medicine: How can regulatory science help?

2018 ◽  
Vol 2 (5) ◽  
pp. 295-300
Author(s):  
Joan E. Adamo ◽  
Robert V. Bienvenu ◽  
F. Owen Fields ◽  
Soma Ghosh ◽  
Christina M. Jones ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Precision Medicine ◽  
Working Group ◽  
Regulatory Science ◽  
Translational Science ◽  
Next Generation ◽  
Clinical Validity ◽  
Knowledge Gaps ◽  
Recent Advances ◽  
Generation Sequencing

Building on the recent advances in next-generation sequencing, the integration of genomics, proteomics, metabolomics, and other approaches hold tremendous promise for precision medicine. The approval and adoption of these rapidly advancing technologies and methods presents several regulatory science considerations that need to be addressed. To better understand and address these regulatory science issues, a Clinical and Translational Science Award Working Group convened the Regulatory Science to Advance Precision Medicine Forum. The Forum identified an initial set of regulatory science gaps. The final set of key findings and recommendations provided here address issues related to the lack of standardization of complex tests, preclinical issues, establishing clinical validity and utility, pharmacogenomics considerations, and knowledge gaps.

scholarly journals Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. e000872
Author(s):  
Samantha O Perakis ◽  
Sabrina Weber ◽  
Qing Zhou ◽  
Ricarda Graf ◽  
Sabine Hojas ◽  
...  
Keyword(s):  
Decision Support ◽  
Next Generation Sequencing ◽  
Metastatic Breast ◽  
Clinical Decision ◽  
Molecular Data ◽  
Current Status ◽  
Precision Oncology ◽  
Next Generation ◽  
Generation Sequencing ◽  
Tier I

ObjectivePrecision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).MethodsIn order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.ResultsEach platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.ConclusionsTreatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.

scholarly journals Next-generation sequencing for endocrine cancers: Recent advances and challenges

Tumor Biology ◽  
2017 ◽  
Vol 39 (5) ◽  
pp. 101042831769837 ◽  
Author(s):  
Padmanaban S Suresh ◽  
Thejaswini Venkatesh ◽  
Rie Tsutsumi ◽  
Abhishek Shetty
Keyword(s):  
Next Generation Sequencing ◽  
Drug Targets ◽  
Current View ◽  
Endocrine Tumors ◽  
Next Generation ◽  
Clinical Genetic ◽  
Clinical Genetic Testing ◽  
Recent Advances ◽  
Microarray Analyses ◽  
Generation Sequencing

Contemporary molecular biology research tools have enriched numerous areas of biomedical research that address challenging diseases, including endocrine cancers (pituitary, thyroid, parathyroid, adrenal, testicular, ovarian, and neuroendocrine cancers). These tools have placed several intriguing clues before the scientific community. Endocrine cancers pose a major challenge in health care and research despite considerable attempts by researchers to understand their etiology. Microarray analyses have provided gene signatures from many cells, tissues, and organs that can differentiate healthy states from diseased ones, and even show patterns that correlate with stages of a disease. Microarray data can also elucidate the responses of endocrine tumors to therapeutic treatments. The rapid progress in next-generation sequencing methods has overcome many of the initial challenges of these technologies, and their advantages over microarray techniques have enabled them to emerge as valuable aids for clinical research applications (prognosis, identification of drug targets, etc.). A comprehensive review describing the recent advances in next-generation sequencing methods and their application in the evaluation of endocrine and endocrine-related cancers is lacking. The main purpose of this review is to illustrate the concepts that collectively constitute our current view of the possibilities offered by next-generation sequencing technological platforms, challenges to relevant applications, and perspectives on the future of clinical genetic testing of patients with endocrine tumors. We focus on recent discoveries in the use of next-generation sequencing methods for clinical diagnosis of endocrine tumors in patients and conclude with a discussion on persisting challenges and future objectives.

scholarly journals Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

2019 ◽  
Vol 10 (7) ◽  
pp. 376-395 ◽  
Author(s):  
Yulia A Nasykhova ◽  
Yury A Barbitoff ◽  
Elena A Serebryakova ◽  
Dmitry S Katserov ◽  
Andrey S Glotov
Keyword(s):  
Type 2 Diabetes ◽  
Next Generation Sequencing ◽  
Genetic Research ◽  
Next Generation ◽  
Recent Advances ◽  
Generation Sequencing

scholarly journals Recent advances in wheat genomics using next generation sequencing

2016 ◽  
Vol 18 (2) ◽  
pp. 78-84
Author(s):  
Shigeo Takumi ◽  
Kentaro Yoshida ◽  
Nobuyuki Mizuno ◽  
Fuminori Kobayashi ◽  
Atsushi Nagano ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Next Generation ◽  
Recent Advances ◽  
Generation Sequencing

scholarly journals treedata.table: a wrapper for data.table that enables fast manipulation of large phylogenetic trees matched to data

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12450
Author(s):  
Cristian Román Palacios ◽  
April Wright ◽  
Josef Uyeda
Keyword(s):  
Next Generation Sequencing ◽  
Phylogenetic Trees ◽  
Next Generation ◽  
Data Repositories ◽  
Data Manipulation ◽  
Link Type ◽  
Recent Advances ◽  
Phylogenetic Data ◽  
Public Data ◽  
Generation Sequencing

The number of terminals in phylogenetic trees has significantly increased over the last decade. This trend reflects recent advances in next-generation sequencing, accessibility of public data repositories, and the increased use of phylogenies in many fields. Despite R being central to the analysis of phylogenetic data, manipulation of phylogenetic comparative datasets remains slow, complex, and poorly reproducible. Here, we describe the first R package extending the functionality and syntax of data.table to explicitly deal with phylogenetic comparative datasets. treedata.table significantly increases speed and reproducibility during the data manipulation steps involved in the phylogenetic comparative workflow in R. The latest release of treedata.table is currently available through CRAN (https://cran.r-project.org/web/packages/treedata.table/). Additional documentation can be accessed through rOpenSci (https://ropensci.github.io/treedata.table/).

scholarly journals Current Status and Prospect of Wheat Functional Genomics using Next Generation Sequencing

2018 ◽  
Vol 50 (4) ◽  
pp. 364-377 ◽  
Author(s):  
Changhyun Choi ◽  
Young-Mi Yoon ◽  
Jae-Han Son ◽  
Seong-Woo Cho ◽  
Chon-Sik Kang
Keyword(s):  
Next Generation Sequencing ◽  
Functional Genomics ◽  
Current Status ◽  
Next Generation ◽  
Generation Sequencing
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