Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data

Galen F Gao; Joel S Parker; Sheila M Reynolds; Tiago C Silva; Liang-Bo Wang; Wanding Zhou; Rehan Akbani; Matthew Bailey; Saianand Balu; Benjamin P Berman; Denise Brooks; Hu Chen; Andrew D Cherniack; John A Demchok; Li Ding; Ina Felau; Sharon Gaheen; Daniela S Gerhard; David I Heiman; Kyle M Hernandez; Katherine A Hoadley; Reyka Jayasinghe; Anab Kemal; Theo A Knijnenburg; Peter W Laird; Michael K A Mensah; Andrew J Mungall; A Gordon Robertson; Hui Shen; Roy Tarnuzzer; Zhining Wang; Matthew Wyczalkowski; Liming Yang; Jean C Zenklusen; Zhenyu Zhang; Genomic Data Analysis Network; Han Liang; Michael S Noble

doi:10.1016/j.cels.2019.06.006

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data

Cell Syst. 2019 Jul 24;9(1):24-34.e10. doi: 10.1016/j.cels.2019.06.006.

Authors

Galen F Gao¹, Joel S Parker², Sheila M Reynolds³, Tiago C Silva⁴, Liang-Bo Wang⁵, Wanding Zhou⁶, Rehan Akbani⁷, Matthew Bailey⁵, Saianand Balu⁸, Benjamin P Berman⁹, Denise Brooks¹⁰, Hu Chen¹¹, Andrew D Cherniack¹², John A Demchok¹³, Li Ding⁵, Ina Felau¹³, Sharon Gaheen¹⁴, Daniela S Gerhard¹³, David I Heiman¹⁵, Kyle M Hernandez¹⁶, Katherine A Hoadley², Reyka Jayasinghe¹⁷, Anab Kemal¹³, Theo A Knijnenburg³, Peter W Laird⁶, Michael K A Mensah¹³, Andrew J Mungall¹⁰, A Gordon Robertson¹⁰, Hui Shen⁶, Roy Tarnuzzer¹³, Zhining Wang¹³, Matthew Wyczalkowski⁵, Liming Yang¹³, Jean C Zenklusen¹³, Zhenyu Zhang¹⁸; Genomic Data Analysis Network; Han Liang¹⁹, Michael S Noble²⁰

Affiliations

¹ Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA; The University of Texas Southwestern Medical School, Dallas, TX 75390, USA.
² Department of Genetics, Lineberger Comprehensive Cancer Center, the University of North Carolin at Chapel Hill, Chapel Hill, NC 27599, USA.
³ Institute for Systems Biology, Seattle, WA 98109, USA.
⁴ Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP 14.040-905, Brazil.
⁵ Department of Medicine, Washington University in St Louis, Saint Louis, MO 63108, USA; McDonnell Genome Institute, Washington University in St Louis, Saint Louis, MO 63108, USA; Siteman Cancer Center, Washington University in St Louis, Saint Louis, MO 63108, USA.
⁶ Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI 49503, USA.
⁷ Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
⁸ Lineberger Comprehensive Cancer Center, Bioinformatics Core, the University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁹ Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Faculty of Medicine, Department of Developmental Biology and Cancer Research, the Hebrew University of Jerusalem, Jerusalem 91120, Israel.
¹⁰ Canada's Michael Smith Genome Sciences Centre, Vancouver, BC V5Z 4S6, Canada.
¹¹ Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA.
¹² Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
¹³ National Cancer Institute, Bethesda, MD 20892, USA.
¹⁴ Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc., Frederick, MD 21702, USA.
¹⁵ Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA.
¹⁶ Department of Pediatrics, the University of Chicago, Chicago, IL 60637, USA; Center for Research Informatics, the University of Chicago, Chicago, IL 60637, USA.
¹⁷ Department of Medicine, Washington University in St Louis, Saint Louis, MO 63108, USA.
¹⁸ Center for Translational Data Science, the University of Chicago, Chicago, IL 60615, USA.
¹⁹ Department of Bioinformatics and Computational Biology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA; Department of Systems Biology, the University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. Electronic address: hliang1@mdanderson.org.
²⁰ Eli and Edythe L. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA. Electronic address: mnoble@cogenimmune.com.

Abstract

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

Keywords: DNA methylation; The Cancer Genome Atlas; human reference genome; mRNA expression; microRNA expression; quality control; somatic copy number alteration; somatic mutation.

Publication types

Comparative Study
Research Support, N.I.H., Extramural

MeSH terms

Controlled Before-After Studies
Datasets as Topic
Gene Expression Profiling
Genome / genetics*
Genome, Human
Genomics
Health Information Exchange
High-Throughput Nucleotide Sequencing
Humans
MicroRNAs / genetics*
Molecular Sequence Annotation
Neoplasms / genetics*
Reproducibility of Results
Software*

Substances

MicroRNAs

Abstract

Publication types

MeSH terms

Substances

Grants and funding