Non-negligible Occurrence of Errors in Gender Description in Public Data Sets
Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public dataset...
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BioMed Central
2016-03-01
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Series: | Genomics & Informatics |
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Online Access: | http://genominfo.org/upload/pdf/gni-14-34.pdf |
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author | Jong Hwan Kim Jong-Luyl Park Seon-Young Kim |
author_facet | Jong Hwan Kim Jong-Luyl Park Seon-Young Kim |
author_sort | Jong Hwan Kim |
collection | DOAJ |
description | Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public datasets, we observed that errors in gender information occur quite often in public datasets. When we analyzed the gender description and the methylation patterns of gender-specific probes (glucose-6-phosphate dehydrogenase [G6PD], ephrin-B1 [EFNB1], and testis specific protein, Y-linked 2 [TSPY2]) in 5,611 samples produced using Infinium 450K HumanMethylation arrays, we found that 19 samples from 7 datasets were erroneously described. We also analyzed 1,819 samples produced using the Affymetrix U133Plus2 array using several gender-specific genes (X (inactive)-specific transcript [XIST], eukaryotic translation initiation factor 1A, Y-linked [EIF1AY], and DEAD [Asp-Glu-Ala-Asp] box polypeptide 3, Y-linked [DDDX3Y]) and found that 40 samples from 3 datasets were erroneously described. We suggest that the users of public datasets should not expect that the data are error-free and, whenever possible, that they should check the consistency of the data. |
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institution | Kabale University |
issn | 1598-866X 2234-0742 |
language | English |
publishDate | 2016-03-01 |
publisher | BioMed Central |
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series | Genomics & Informatics |
spelling | doaj-art-cabc725b0e4d42e7b07946fd208059182025-02-02T10:53:20ZengBioMed CentralGenomics & Informatics1598-866X2234-07422016-03-01141344010.5808/GI.2016.14.1.34188Non-negligible Occurrence of Errors in Gender Description in Public Data SetsJong Hwan Kim0Jong-Luyl Park1Seon-Young Kim2Genome Structure Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Korea.Epigenome Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Korea.Genome Structure Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Korea.Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public datasets, we observed that errors in gender information occur quite often in public datasets. When we analyzed the gender description and the methylation patterns of gender-specific probes (glucose-6-phosphate dehydrogenase [G6PD], ephrin-B1 [EFNB1], and testis specific protein, Y-linked 2 [TSPY2]) in 5,611 samples produced using Infinium 450K HumanMethylation arrays, we found that 19 samples from 7 datasets were erroneously described. We also analyzed 1,819 samples produced using the Affymetrix U133Plus2 array using several gender-specific genes (X (inactive)-specific transcript [XIST], eukaryotic translation initiation factor 1A, Y-linked [EIF1AY], and DEAD [Asp-Glu-Ala-Asp] box polypeptide 3, Y-linked [DDDX3Y]) and found that 40 samples from 3 datasets were erroneously described. We suggest that the users of public datasets should not expect that the data are error-free and, whenever possible, that they should check the consistency of the data.http://genominfo.org/upload/pdf/gni-14-34.pdfbloodDNA methylationgender identitygene expressionmicroarray analysis |
spellingShingle | Jong Hwan Kim Jong-Luyl Park Seon-Young Kim Non-negligible Occurrence of Errors in Gender Description in Public Data Sets Genomics & Informatics blood DNA methylation gender identity gene expression microarray analysis |
title | Non-negligible Occurrence of Errors in Gender Description in Public Data Sets |
title_full | Non-negligible Occurrence of Errors in Gender Description in Public Data Sets |
title_fullStr | Non-negligible Occurrence of Errors in Gender Description in Public Data Sets |
title_full_unstemmed | Non-negligible Occurrence of Errors in Gender Description in Public Data Sets |
title_short | Non-negligible Occurrence of Errors in Gender Description in Public Data Sets |
title_sort | non negligible occurrence of errors in gender description in public data sets |
topic | blood DNA methylation gender identity gene expression microarray analysis |
url | http://genominfo.org/upload/pdf/gni-14-34.pdf |
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