Eun Bit Bae1,2, Sejin Nam3, Sungin Lee1, Sun-Ju Ahn4. 1. Institute of Quantum Biophysics, Sungkyunkwan University, 16419, Seoul, Gyeonggi-do, Republic of Korea. 2. Department of Psychiatry, Research Institute for Medical Bigdata Science, Korea University Anam Hospital, Seoul, Republic of Korea. 3. Department of Global Convergence, Sungkyunkwan UniversityR&D Center, ezCaretech Co., Ltd, 03063, Seoul, Jongno-gu, Republic of Korea. 4. Institute of Quantum Biophysics, Sungkyunkwan University, 16419, Seoul, Gyeonggi-do, Republic of Korea. april0149@gmail.com.
Abstract
BACKGROUND: Biotechnology in genomics, such as sequencing devices and gene quantification software, has proliferated and been applied to clinical settings. However, the lack of standards applicable to it poses practical problems in interoperability and reusability of the technology across various application domains. This study aims to visualize and identify the standard trends in clinical genomics and to suggest areas on which standardization efforts must focus. METHODS: Of 16,538 articles retrieved from PubMed, published from 1975 to 2020, using search keywords "genomics and standard" and "clinical genomic sequence and standard", terms were extracted from the abstracts and titles of 15,855 articles. Our analysis includes (1) network analysis of full phases (2) period analysis with five phases; (3) statistical analysis; (4) content analysis. RESULTS: Our research trend showed an increasing trend from 2003, years marked by the completion of the human genome project (2003). The content analysis showed that keywords related to such concepts as gene types for analysis, and analysis techniques were increased in phase 3 when US-FDA first approved the next-generation sequencer. During 2017-2019, oncology-relevant terms were clustered and contributed to the increasing trend in phase 4 of the content analysis. In the statistical analysis, all the categories showed high regression values (R2 > 0.586) throughout the whole analysis period and phase-based statistical analysis showed significance only in the Genetics terminology category (P = .039*) at phase 4. CONCLUSIONS: Through comprehensive trend analysis from our study, we provided the trend shifts and high-demand items in standardization for clinical genetics.
BACKGROUND: Biotechnology in genomics, such as sequencing devices and gene quantification software, has proliferated and been applied to clinical settings. However, the lack of standards applicable to it poses practical problems in interoperability and reusability of the technology across various application domains. This study aims to visualize and identify the standard trends in clinical genomics and to suggest areas on which standardization efforts must focus. METHODS: Of 16,538 articles retrieved from PubMed, published from 1975 to 2020, using search keywords "genomics and standard" and "clinical genomic sequence and standard", terms were extracted from the abstracts and titles of 15,855 articles. Our analysis includes (1) network analysis of full phases (2) period analysis with five phases; (3) statistical analysis; (4) content analysis. RESULTS: Our research trend showed an increasing trend from 2003, years marked by the completion of the human genome project (2003). The content analysis showed that keywords related to such concepts as gene types for analysis, and analysis techniques were increased in phase 3 when US-FDA first approved the next-generation sequencer. During 2017-2019, oncology-relevant terms were clustered and contributed to the increasing trend in phase 4 of the content analysis. In the statistical analysis, all the categories showed high regression values (R2 > 0.586) throughout the whole analysis period and phase-based statistical analysis showed significance only in the Genetics terminology category (P = .039*) at phase 4. CONCLUSIONS: Through comprehensive trend analysis from our study, we provided the trend shifts and high-demand items in standardization for clinical genetics.
Authors: Bruce D Cheson; John M Bennett; Kenneth J Kopecky; Thomas Büchner; Cheryl L Willman; Elihu H Estey; Charles A Schiffer; Hartmut Doehner; Martin S Tallman; T Andrew Lister; Francesco Lo-Coco; Roel Willemze; Andrea Biondi; Wolfgang Hiddemann; Richard A Larson; Bob Löwenberg; Miguel A Sanz; David R Head; Ryuzo Ohno; Clara D Bloomfield; Francesco LoCocco Journal: J Clin Oncol Date: 2003-12-15 Impact factor: 44.544
Authors: Elizabeth M McCormick; Marie T Lott; Matthew C Dulik; Lishuang Shen; Marcella Attimonelli; Ornella Vitale; Amel Karaa; Renkui Bai; Daniel E Pineda-Alvarez; Larry N Singh; Christine M Stanley; Stacey Wong; Anshu Bhardwaj; Daria Merkurjev; Rong Mao; Neal Sondheimer; Shiping Zhang; Vincent Procaccio; Douglas C Wallace; Xiaowu Gai; Marni J Falk Journal: Hum Mutat Date: 2020-11-10 Impact factor: 4.878