| The sva package for removing batch effects and other unwanted variation in high-throughput experiments JT Leek, WE Johnson, HS Parker, AE Jaffe, JD Storey Bioinformatics 28 (6), 882-883, 2012 | 4438 | 2012 |
| sva: Surrogate variable analysis JT Leek, WE Johnson, HS Parker, EJ Fertig, AE Jaffe, JD Storey, Y Zhang, ... R package version 3 (0), 882-883, 2019 | 462 | 2019 |
| Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction HS Parker, JT Leek, AV Favorov, M Considine, X Xia, S Chavan, ... Bioinformatics 30 (19), 2757-2763, 2014 | 112 | 2014 |
| sva: Surrogate Variable Analysis R package version 3.10. 0 JT Leek, WE Johnson, HS Parker, EJ Fertig, AE Jaffe, JD Storey, Y Zhang, ... DOI10 B 9, 2014 | 88 | 2014 |
| Removing batch effects for prediction problems with frozen surrogate variable analysis HS Parker, HC Bravo, JT Leek PeerJ 2, e561, 2014 | 73 | 2014 |
| The practical effect of batch on genomic prediction HS Parker, JT Leek Statistical applications in genetics and molecular biology 11 (3), 2012 | 37 | 2012 |
| SVA: Surrogate Variable Analysis (2019) JT Leek, WE Johnson, HS Parker, EJ Fertig, AE Jaffe, JD Storey, Y Zhang, ... R package version 3 (0), 25-27, 0 | 27 | |
| Opinionated analysis development H Parker PeerJ Preprints 5, e3210v1, 2017 | 20 | 2017 |
| Perspective on data science RD Peng, HS Parker Annual Review of Statistics and Its Application 9, 1-20, 2022 | 6 | 2022 |
| AGA: interactive pipeline for reproducible gene expression and DNA methylation data analyses M Considine, H Parker, Y Wei, X Xia, L Cope, M Ochs, E Fertig F1000Research 4, 2015 | 3 | 2015 |
| Writing R Package from scratch H Parker | 3 | 2014 |
| Not so standard deviations podcast, episodes on design thinking (episodes 63–69) R Peng, H Parker | 2 | 2018 |
| Sva JT Leek, WE Johnson, HS Parker, EJ Fertig, AE Jaffe, JD Storey Bioconductor, 2017 | 2 | 2017 |
| Package ‘sva’ JT Leek, WE Johnson, HS Parker, EJ Fertig, AE Jaffe, JD Storey, Y Zhang, ... | 1 | 2014 |
| EXTENDING MACHINE LEARNING TRAINING DATA TO GENERATE AN ARTIFICIAL INTELLIGENCE RECOMMENDATION ENGINE HS Parker, AM Barros US Patent US-20210342917-A1, 2021 | | 2021 |
| A Design Mindset for Working with Data H Parker Plant Health 2019, 2019 | | 2019 |
| AGA: Interactive pipeline for reproducible genomics analyses [version 1; peer review: 2 approved] M Considine, H Parker, Y Wei, X Xia, L Cope, M Ochs, E Fertig | | 2015 |
| AGA M Considine, H Parker, Y Wei, X Xia, L Cope, MF Ochs, E Fertig F1000Research 4, 2015 | | 2015 |
| Practical statistical issues in translational genomics HS Parker The Johns Hopkins University, 2013 | | 2013 |
Jeff LeekChief Data Officer, VP, and J Orin Edson Foundation Professor, Fred Hutchinson Cancer CenterVerified email at fredhutch.org
