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Full-Text Articles in Genomics
Higher Entropy Observed In Sars-Cov-2 Genomes From The First Covid-19 Wave In Pakistan, Najia Karim Ghanchi, Asghar Nasir, Kiran I. Masood, Syed Hani Abidi, Syed Faisal Mahmood, Akber Kanji, Safina Abdul Razzak, Waqasuddin Khan, Saba Shahid, Maliha Yameen, Ali Raza, Javaria Ashraf, Zeeshan Ansar Ahmed, Mohammad Buksh Dharejo, Nazneen Islam, Zahra Hasan, Rumina Hasan
Higher Entropy Observed In Sars-Cov-2 Genomes From The First Covid-19 Wave In Pakistan, Najia Karim Ghanchi, Asghar Nasir, Kiran I. Masood, Syed Hani Abidi, Syed Faisal Mahmood, Akber Kanji, Safina Abdul Razzak, Waqasuddin Khan, Saba Shahid, Maliha Yameen, Ali Raza, Javaria Ashraf, Zeeshan Ansar Ahmed, Mohammad Buksh Dharejo, Nazneen Islam, Zahra Hasan, Rumina Hasan
Department of Pathology and Laboratory Medicine
Background: We investigated the genome diversity of SARS-CoV-2 associated with the early COVID-19 period to investigate evolution of the virus in Pakistan.
Materials and methods: We studied ninety SARS-CoV-2 strains isolated between March and October 2020. Whole genome sequences from our laboratory and available genomes were used to investigate phylogeny, genetic variantion and mutation rates of SARS-CoV-2 strains in Pakistan. Site specific entropy analysis compared mutation rates between strains isolated before and after June 2020.
Results: In March, strains belonging to L, S, V and GH clades were observed but by October, only L and GH strains were present. The …
Methylation Of Leukocyte Dna And Ovarian Cancer: Relationships With Disease Status And Outcome, Brooke L. Fridley, Sebastian M. Armasu, Mine S. Cicek, Melissa C. Larson, Chen Wang, Stacey J. Winham, Kimberly R. Kalli, Devin C. Koestler
Methylation Of Leukocyte Dna And Ovarian Cancer: Relationships With Disease Status And Outcome, Brooke L. Fridley, Sebastian M. Armasu, Mine S. Cicek, Melissa C. Larson, Chen Wang, Stacey J. Winham, Kimberly R. Kalli, Devin C. Koestler
Dartmouth Scholarship
Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions. We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival.
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
How To Get The Most From Microarray Data: Advice From Reverse Genomics, Ivan P. Gorlov, Ji-Yeon Yang, Jinyoung Byun, Christopher Logothetis, Olga Y. Gorlova, Kim-Anh Do, Christopher Amos
Dartmouth Scholarship
Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data–derived predictor of known cancer associated genes. We found that the traditional approach of identifying cancer genes—identifying differentially expressed genes—is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results …
Technical Desiderata For The Integration Of Genomic Data Into Electronic Health Records., Daniel R Masys, Gail P Jarvik, Neil F Abernethy, Nicholas R Anderson, George J Papanicolaou, Dina N Paltoo, Mark A Hoffman, Isaac S Kohane, Howard P Levy
Technical Desiderata For The Integration Of Genomic Data Into Electronic Health Records., Daniel R Masys, Gail P Jarvik, Neil F Abernethy, Nicholas R Anderson, George J Papanicolaou, Dina N Paltoo, Mark A Hoffman, Isaac S Kohane, Howard P Levy
Manuscripts, Articles, Book Chapters and Other Papers
The era of "Personalized Medicine," guided by individual molecular variation in DNA, RNA, expressed proteins and other forms of high volume molecular data brings new requirements and challenges to the design and implementation of Electronic Health Records (EHRs). In this article we describe the characteristics of biomolecular data that differentiate it from other classes of data commonly found in EHRs, enumerate a set of technical desiderata for its management in healthcare settings, and offer a candidate technical approach to its compact and efficient representation in operational systems.