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National Institute of Environmental Health Sciences

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Publication Detail

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

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

Published In Cell Syst, (2019 07 24)

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.

PubMed ID: 31344359 Exiting the NIEHS site

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

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