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Sarah A. Pendergrass
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Journal Articles
- 2021
- [j14]Ning Shang
, Atlas Khan, Fernanda Polubriaginof, Francesca Zanoni, Karla Mehl, David Fasel, Paul E. Drawz, Robert J. Carroll, Joshua C. Denny
, Matthew A. Hathcock, Adelaide M. Arruda-Olson, Peggy L. Peissig, Richard A. Dart, Murray H. Brilliant, Eric B. Larson, David S. Carrell, Sarah A. Pendergrass, Shefali Setia Verma, Marylyn D. Ritchie, Barbara Benoit, Vivian S. Gainer, Elizabeth W. Karlson, Adam S. Gordon
, Gail P. Jarvik, Ian B. Stanaway, David R. Crosslin, Sumit Mohan
, Iuliana Ionita-Laza, Nicholas P. Tatonetti, Ali G. Gharavi, George Hripcsak, Chunhua Weng, Krzysztof Kiryluk:
Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies. npj Digit. Medicine 4 (2021) - 2019
- [j13]Xinyuan Zhang, Anna Okula Basile, Sarah A. Pendergrass
, Marylyn D. Ritchie:
Real world scenarios in rare variant association analysis: the impact of imbalance and sample size on the power in silico. BMC Bioinform. 20(1): 46:1-46:10 (2019) - 2018
- [j12]Anurag Verma
, Yukiko Bradford, Scott M. Dudek, Anastasia Lucas, Shefali S. Verma, Sarah A. Pendergrass
, Marylyn D. Ritchie:
A simulation study investigating power estimates in phenome-wide association studies. BMC Bioinform. 19(1): 120:1-120:8 (2018) - 2016
- [j11]Anna L. Tyler, Dana C. Crawford
, Sarah A. Pendergrass
:
The detection and characterization of pleiotropy: discovery, progress, and promise. Briefings Bioinform. 17(1): 13-22 (2016) - [j10]Mariusz Butkiewicz, Jessica Cooke Bailey
, Alex T. Frase, Scott M. Dudek, Brian L. Yaspan
, Marylyn D. Ritchie, Sarah A. Pendergrass
, Jonathan L. Haines:
Pathway analysis by randomization incorporating structure - PARIS: an update. Bioinform. 32(15): 2361-2363 (2016) - 2015
- [j9]Logan Dumitrescu, Nicole A. Restrepo, Robert J. Goodloe, Jonathan Boston, Eric Farber-Eger, Sarah A. Pendergrass
, William S. Bush
, Dana C. Crawford
:
Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry. BioData Min. 8: 35 (2015) - 2014
- [j8]Sabrina L. Mitchell
, Jacob B. Hall, Robert J. Goodloe, Jonathan Boston, Eric Farber-Eger, Sarah A. Pendergrass
, William S. Bush
, Dana C. Crawford
:
Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies. BioData Min. 7: 6 (2014) - [j7]Timothy H. Ciesielski, Sarah A. Pendergrass
, Marquitta J. White, Nuri Kodaman, Rafal S. Sobota
, Minjun Huang, Jacquelaine Bartlett, Jing Li, Qinxin Pan, Jiang Gui, Scott B. Selleck, Christopher I. Amos, Marylyn D. Ritchie, Jason H. Moore
, Scott M. Williams
:
Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors. BioData Min. 7: 10 (2014) - [j6]Do Kyoon Kim, Ruowang Li, Scott M. Dudek, Alex T. Frase, Sarah A. Pendergrass
, Marylyn D. Ritchie:
Knowledge-driven genomic interactions: an application in ovarian cancer. BioData Min. 7: 20 (2014) - [j5]Emily Rose Holzinger, Scott M. Dudek, Alex T. Frase, Sarah A. Pendergrass
, Marylyn D. Ritchie:
ATHENA: the analysis tool for heritable and environmental network associations. Bioinform. 30(5): 698-705 (2014) - 2013
- [j4]Daniel Wolfe, Scott M. Dudek, Marylyn D. Ritchie, Sarah A. Pendergrass
:
Visualizing genomic information across chromosomes with PhenoGram. BioData Min. 6: 18 (2013) - [j3]Sarah A. Pendergrass
, Alex T. Frase, John R. Wallace, Daniel Wolfe, Neerja Katiyar, Carrie Moore, Marylyn D. Ritchie:
Genomic analyses with biofilter 2.0: knowledge driven filtering, annotation, and model development. BioData Min. 6: 25 (2013) - 2012
- [j2]Sarah A. Pendergrass
, Scott M. Dudek, Dana C. Crawford
, Marylyn D. Ritchie:
Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View. BioData Min. 5: 5 (2012) - 2010
- [j1]Sarah A. Pendergrass
, Scott M. Dudek, Dana C. Crawford
, Marylyn D. Ritchie:
Synthesis-View: visualization and interpretation of SNP association results for multi-cohort, multi-phenotype data and meta-analysis. BioData Min. 3: 10 (2010)
Conference and Workshop Papers
- 2019
- [c18]William G. La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass:
Interpretation of machine learning predictions for patient outcomes in electronic health records. AMIA 2019 - [c17]Xinyuan Zhang, Yogasudha Veturi, Shefali Setia Verma, William Bone, Anurag Verma, Anastasia Lucas, Scott J. Hebbring, Joshua C. Denny, Ian B. Stanaway, Gail P. Jarvik, David R. Crosslin, Eric B. Larson, Laura Rasmussen-Torvik, Sarah A. Pendergrass, Jordan W. Smoller, Hakon Hakonarson, Patrick Sleiman, Chunhua Weng, David Fasel, Wei-Qi Wei, Iftikhar J. Kullo, Daniel J. Schaid, Wendy K. Chung, Marylyn D. Ritchie:
Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43, 870 individuals from the eMERGE network. PSB 2019: 272-283 - 2017
- [c16]Anna Okula Basile, Anurag Verma, Marta Byrska-Bishop, Sarah A. Pendergrass, Christian Darabos, H. Lester Kirchner:
Session Introduction. PSB 2017: 177-183 - [c15]Christopher R. Bauer, Daniel R. Lavage, John Snyder, Joseph B. Leader, J. Matthew Mahoney, Sarah A. Pendergrass:
Opening the Door to the Large Scale Use of Clinical Lab Measures for Association Testing: Exploring Different Methods for Defining Phenotypes. PSB 2017: 356-367 - [c14]Shefali S. Verma, Anastasia Lucas, Daniel R. Lavage, Joseph B. Leader, Raghu Metpally, Sarathbabu Krishnamurthy, Frederick E. Dewey, Ingrid B. Borecki, Alexander E. Lopez, John D. Overton, John Penn, Jeffrey G. Reid, Sarah A. Pendergrass, Gerda Breitwieser, Marylyn D. Ritchie:
Identifying Genetic Associations with Variability in Metabolic Health and Blood Count Laboratory Values: Diving into the Quantitative Traits by Leveraging Longitudinal Data from an EHR. PSB 2017: 533-544 - 2016
- [c13]Shefali S. Verma, Alex T. Frase, Anurag Verma, Sarah A. Pendergrass, Shaun Mahony, David W. Haas, Marylyn D. Ritchie:
Phenome-Wide Interaction Study (PheWIS) in Aids Clinical Trials Group Data (ACTG). PSB 2016: 57-68 - [c12]Anurag Verma, Joseph B. Leader, Shefali S. Verma, Alex T. Frase, John R. Wallace, Scott M. Dudek, Daniel R. Lavage, Cristopher V. Van Hout, Frederick E. Dewey, John Penn, Alexander E. Lopez, John D. Overton, David J. Carey, David H. Ledbetter, H. Lester Kirchner, Marylyn D. Ritchie, Sarah A. Pendergrass:
Integrating Clinical Laboratory Measures and ICD-9 Code Diagnoses in Phenome-Wide Association Studies. PSB 2016: 168-179 - 2015
- [c11]Joseph B. Leader, Sarah A. Pendergrass, Anurag Verma, David J. Carey, Dustin N. Hartzel, Marylyn D. Ritchie, H. Lester Kirchner:
Contrasting Association Results Between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes. AMIA 2015 - [c10]Molly A. Hall, Shefali S. Verma, Dennis P. Wall, Jason H. Moore, Brendan Keating, Daniel B. Campbell, Gregory Gibson, Folkert W. Asselbergs, Sarah A. Pendergrass:
Session Introduction. Pacific Symposium on Biocomputing 2015: 156-160 - 2014
- [c9]Anna L. Tyler, Dana C. Crawford, Sarah A. Pendergrass:
Session introduction. Pacific Symposium on Biocomputing 2014: 183-187 - [c8]Sarah A. Pendergrass, Santhosh Girirajan, Scott B. Selleck:
Uncovering the Etiology of Autism Spectrum Disorders: Genomics, Bioinformatics, Environment, Data Collection and Exploration, and Future Possibilities. Pacific Symposium on Biocomputing 2014: 422-426 - 2013
- [c7]Sarah A. Pendergrass, Shefali S. Verma, Emily Rose Holzinger, Carrie Moore, John R. Wallace, Scott M. Dudek, Wayne Huggins, Terrie E. Kitchner, Carol Waudby, Richard L. Berg, Catherine A. McCarty, Marylyn D. Ritchie:
Next-Generation Analysis of Cataracts: Determining Knowledge Driven Gene-Gene Interactions Using Biofilter, and Gene-Environment Interactions Using the PhenX Toolkit. Pacific Symposium on Biocomputing 2013: 147-158 - [c6]Carrie Moore, John R. Wallace, Alex T. Frase, Sarah A. Pendergrass, Marylyn D. Ritchie:
Using BioBin to Explore Rare Variant Population Stratification. Pacific Symposium on Biocomputing 2013: 332-343 - 2012
- [c5]Carrie C. Buchanan, John R. Wallace, Alex T. Frase, Eric Torstenson, Sarah A. Pendergrass
, Marylyn D. Ritchie:
A Biologically Informed Method for Detecting Associations with Rare Variants. EvoBIO 2012: 201-210 - 2011
- [c4]Chun-Nan Hsu, Cheng-Ju Kuo, Congxing Cai, Sarah A. Pendergrass, Marylyn D. Ritchie, José Luis Ambite:
Learning Phenotype Mapping for Integrating Large Genetic Data. BioNLP@ACL 2011: 19-27 - [c3]Sarah A. Pendergrass, Scott M. Dudek, Dan M. Roden, Dana C. Crawford, Marylyn D. Ritchie:
Visual Integration of Results from a Large Dna Biobank (Biovu) Using Synthesis-View. Pacific Symposium on Biocomputing 2011: 265-275 - 2004
- [c2]Paul M. Meaney, Qianqian Fang, Margaret Fanning, Sarah A. Pendergrass, Timothy Raynolds, Colleen Fox, Keith D. Paulsen:
Microwave Breast Imaging with an Under-Determined Reconstruction Parameter Mesh. ISBI 2004: 1369-1372 - 2002
- [c1]Dun Li, Paul M. Meaney, Margaret Fanning, Qianqian Fang, Sarah A. Pendergrass
, Timothy Raynolds:
Spectrum analysis of microwave breast examination data and reconstructed images. ISBI 2002: 62-65
Informal and Other Publications
- 2019
- [i1]William G. La Cava, Christopher R. Bauer, Jason H. Moore, Sarah A. Pendergrass:
Interpretation of machine learning predictions for patient outcomes in electronic health records. CoRR abs/1903.12074 (2019)
Coauthor Index
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