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

The Genomic Data Analysis Network

doi:10.1016/j.cels.2019.06.006

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

The Genomic Data Analysis Network

Department of Developmental Biology and Cancer Research

Research output: Contribution to journal › Article › peer-review

109 Scopus citations

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. Gao et al. performed a systematic analysis of the effects of synchronizing the large-scale, widely used, multi-omic dataset of The Cancer Genome Atlas to the current human reference genome. For each of the five molecular data platforms assessed, they demonstrated a very high concordance between the ‘legacy’ GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as ‘harmonized’ by the Genomic Data Commons.

Original language	English
Pages (from-to)	24-34.e10
Journal	Cell Systems
Volume	9
Issue number	1
DOIs	https://doi.org/10.1016/j.cels.2019.06.006
State	Published - 24 Jul 2019

Bibliographical note

Publisher Copyright:
© 2019 The Authors

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.cels.2019.06.006

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title = "Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons{\textquoteright} Data",

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 {\textquoteleft}legacy{\textquoteright} GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as {\textquoteleft}harmonized{\textquoteright} 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. Gao et al. performed a systematic analysis of the effects of synchronizing the large-scale, widely used, multi-omic dataset of The Cancer Genome Atlas to the current human reference genome. For each of the five molecular data platforms assessed, they demonstrated a very high concordance between the {\textquoteleft}legacy{\textquoteright} GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as {\textquoteleft}harmonized{\textquoteright} by the Genomic Data Commons.",

keywords = "DNA methylation, The Cancer Genome Atlas, human reference genome, mRNA expression, microRNA expression, quality control, somatic copy number alteration, somatic mutation",

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

note = "Publisher Copyright: {\textcopyright} 2019 The Authors",

year = "2019",

month = jul,

day = "24",

doi = "10.1016/j.cels.2019.06.006",

language = "אנגלית",

volume = "9",

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journal = "Cell Systems",

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AU - Gao, Galen F.

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AU - Reynolds, Sheila M.

AU - Silva, Tiago C.

AU - Wang, Liang Bo

AU - Zhou, Wanding

AU - Akbani, R.

AU - Bailey, Matthew

AU - Balu, Saianand

AU - Berman, Benjamin P.

AU - Brooks, Denise

AU - Chen, Hu

AU - Cherniack, Andrew D.

AU - Demchok, John A.

AU - Ding, Li

AU - Felau, Ina

AU - Gaheen, Sharon

AU - Gerhard, Daniela S.

AU - Heiman, David I.

AU - Hernandez, Kyle M.

AU - Hoadley, Katherine A.

AU - Jayasinghe, R.

AU - Kemal, Anab

AU - Knijnenburg, Theo A.

AU - Laird, Peter W.

AU - Mensah, Michael K.A.

AU - Mungall, Andrew J.

AU - Robertson, A. Gordon

AU - Shen, Hui

AU - Tarnuzzer, Roy

AU - Wang, Zhining

AU - Wyczalkowski, Matthew

AU - Yang, Liming

AU - Zenklusen, Jean C.

AU - Zhang, Zhenyu

AU - Liang, Han

AU - Noble, Michael S.

PY - 2019/7/24

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AB - 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. Gao et al. performed a systematic analysis of the effects of synchronizing the large-scale, widely used, multi-omic dataset of The Cancer Genome Atlas to the current human reference genome. For each of the five molecular data platforms assessed, they demonstrated a very high concordance between the ‘legacy’ GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as ‘harmonized’ by the Genomic Data Commons.

KW - DNA methylation

KW - The Cancer Genome Atlas

KW - human reference genome

KW - mRNA expression

KW - microRNA expression

KW - quality control

KW - somatic copy number alteration

KW - somatic mutation

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SN - 2405-4712

VL - 9

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JO - Cell Systems

JF - Cell Systems

IS - 1

ER -

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

Abstract

Bibliographical note

Keywords

UN SDGs

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