Browsing by Author "Varghese, Ronnie"

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    CAGm: A repository of germline microsatellite variations in the 1000 genomes project
    Kinney, N.; Titus-Glover, K.; Wren, J.D.; Varghese, Ronnie; Michalak, Pawel; Liao, H.; Anandakrishnan, Ramu; Pulenthiran, A.; Kang, L.; Garner, Harold R. (Oxford University Press, 2019-01-08)
    The human genome harbors an abundance of repetitive DNA; however, its function continues to be debated. Microsatellites-a class of short tandem repeat-are established as an important source of genetic variation. Array length variants are common among microsatellites and affect gene expression; but, efforts to understand the role and diversity of microsatellite variation has been hampered by several challenges. Without adequate depth, both long-read and short-read sequencing may not detect the variants present in a sample; additionally, large sample sizes are needed to reveal the degree of population-level polymorphism. To address these challenges we present the Comparative Analysis of Germline Microsatellites (CAGm): A database of germline microsatellites from 2529 individuals in the 1000 genomes project. A key novelty of CAGm is the ability to aggregate microsatellite variation by population, ethnicity (super population) and gender. The database provides advanced searching for microsatellites embedded in genes and functional elements. All data can be downloaded as Microsoft Excel spreadsheets. Two use-case scenarios are presented to demonstrate its utility: A mononucleotide (A) microsatellite at the BAT-26 locus and a dinucleotide (CA) microsatellite in the coding region of FGFRL1. CAGm is freely available at http://www.cagmdb.org/. © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.
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    Differentiating between cancer and normal tissue samples using multi-hit combinations of genetic mutations
    Dash, Sajal; Kinney, N.A.; Varghese, Ronnie; Garner, Harold R.; Feng, Wu-chun; Anandakrishnan, Ramu (Nature Publishing Group, 2019-01-30)
    Cancer is known to result from a combination of a small number of genetic defects. However, the specific combinations of mutations responsible for the vast majority of cancers have not been identified. Current computational approaches focus on identifying driver genes and mutations. Although individually these mutations can increase the risk of cancer they do not result in cancer without additional mutations. We present a fundamentally different approach for identifying the cause of individual instances of cancer: we search for combinations of genes with carcinogenic mutations (multi-hit combinations) instead of individual driver genes or mutations. We developed an algorithm that identified a set of multi-hit combinations that differentiate between tumor and normal tissue samples with 91% sensitivity (95% Confidence Interval (CI) = 89–92%) and 93% specificity (95% CI = 91–94%) on average for seventeen cancer types. We then present an approach based on mutational profile that can be used to distinguish between driver and passenger mutations within these genes. These combinations, with experimental validation, can aid in better diagnosis, provide insights into the etiology of cancer, and provide a rational basis for designing targeted combination therapies. © 2019, The Author(s).
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    Interfacial band alignment and structural properties of nanoscale TiO2 thin films for integration with epitaxial crystallographic oriented germanium
    Jain, Nikhil; Zhu, Yizheng; Maurya, Deepam; Varghese, Ronnie; Priya, Shashank; Hudait, Mantu K. (American Institute of Physics, 2014-01-14)
    We have investigated the structural and band alignment properties of nanoscale titanium dioxide (TiO2) thin films deposited on epitaxial crystallographic oriented Ge layers grown on (100), (110), and (111) A GaAs substrates by molecular beam epitaxy. The TiO2 thin films deposited at low temperature by physical vapor deposition were found to be amorphous in nature, and high-resolution transmission electron microscopy confirmed a sharp heterointerface between the TiO2 thin film and the epitaxially grown Ge with no traceable interfacial layer. A comprehensive assessment on the effect of substrate orientation on the band alignment at the TiO2/Ge heterointerface is presented by utilizing x-ray photoelectron spectroscopy and spectroscopic ellipsometry. A band-gap of 3.33 +/- 0.02 eV was determined for the amorphous TiO2 thin film from the Tauc plot. Irrespective of the crystallographic orientation of the epitaxial Ge layer, a sufficient valence band-offset of greater than 2 eV was obtained at the TiO2/Ge heterointerface while the corresponding conduction band-offsets for the aforementioned TiO2/Ge system were found to be smaller than 1 eV. A comparative assessment on the effect of Ge substrate orientation revealed a valence band-offset relation of Delta E-V(100)> Delta E-V(111)> Delta E-V(110) and a conduction band-offset relation of Delta E-C(110) > Delta E-C(111)> Delta E-C(100). These band-offset parameters are of critical importance and will provide key insight for the design and performance analysis of TiO2 for potential high-k dielectric integration and for future metal-insulator-semiconductor contact applications with next generation of Ge based metal-oxide field-effect transistors. (C) 2014 AIP Publishing LLC.
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    Temperature-time transformation diagram for Pb(Zr,Ti)O-3 thin films
    Varghese, Ronnie; Williams, Matthew; Gupta, Shashaank; Priya, Shashank (American Institute of Physics, 2011-07-01)
    In this paper, we describe an analytical model to define the temperature-time-transformation (TTT) diagram of sol-gel deposited Pb(Zr,Ti)O-3 thin films on platinized silicon substrates. Texture evolution in film occurred as the pyrolysis and thermal annealing conditions were varied. We demonstrate that the developed model can quantitatively predict the outcome of thermal treatment conditions in terms of texture evolution. Multinomial and multivariate regression techniques were utilized to create the predictor models for TTT data. Further, it was found that multinomial regression can provide better fit as compared to standard regression and multivariate regression. We have generalized this approach so that it can be applied to other thin film deposition techniques and bulk ceramics. (C) 2011 American Institute of Physics. [doi:10.1063/1.3606433]