Kwon et al. BMC Genomics (2017) 18:88 DOI 10.1186/s12864-016-3464-x
ERRATUM
Open Access
Erratum to: Integrative analysis of multiomics data for identifying multi-markers for diagnosing pancreatic cancer Min-Seok Kwon1, Yongkang Kim2, Seungyeoun Lee3, Junghyun Namkung4, Taegyun Yun4, Sung Gon Yi4, Sangjo Han4, Meejoo Kang5, Sun Whe Kim5, Jin-Young Jang5* and Taesung Park1,2* Erratum After publication of this article [1] it was brought to the Editors’ attention that there were inaccurate descriptions of validation data in its abstract and list of abbreviations. For the validation, we used the three datasets from Gene Expression Omnibus (GEO), not the Cancer Genome Atlas (TCGA). The corrected description for line 8–10 in abstract is as below: “For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) data depository.” In page 9, the corrected description of list of abbreviations used is as follows: “AUC, Area under curve; BA, Balanced accuracy; BR, Breast cancer; GEO, Gene Expression Omnibus; GO, Gene ontology; HCC, Hepatocellular carcinoma; LC, Lung cancer; LOOCV, Leave-one-out cross-validation; LP, Lymphoma; mRNA, messenger RNA; miRNA, microRNA; PDAC, Pancreatic ductal adenocarcinoma; SVM, Support vector machine;” Author details 1 Interdisciplinary program in Bioinformatics, Seoul National University, Seoul, Korea. 2Department of Statistics, Seoul National University, Seoul, Korea. 3 Department of Mathematics and Statistics, Sejong University, Seoul, Korea. 4 Immunodiagnostics R&D Team, IVD Business Unit, New Business Division, SK telecom Co, Seongnam, Korea. 5Department of Surgery, Seoul National University Hospital, Seoul, Korea. Received: 22 December 2016 Accepted: 22 December 2016
Reference 1. Kwon M-S, et al. Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer. BMC Genomics. 2015;16 Suppl 9:S4. * Correspondence: [email protected]; [email protected] 5 Department of Surgery, Seoul National University Hospital, Seoul, Korea 1 Interdisciplinary program in Bioinformatics, Seoul National University, Seoul, Korea © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
ERRATUM
Open Access
Erratum to: Integrative analysis of multiomics data for identifying multi-markers for diagnosing pancreatic cancer Min-Seok Kwon1, Yongkang Kim2, Seungyeoun Lee3, Junghyun Namkung4, Taegyun Yun4, Sung Gon Yi4, Sangjo Han4, Meejoo Kang5, Sun Whe Kim5, Jin-Young Jang5* and Taesung Park1,2* Erratum After publication of this article [1] it was brought to the Editors’ attention that there were inaccurate descriptions of validation data in its abstract and list of abbreviations. For the validation, we used the three datasets from Gene Expression Omnibus (GEO), not the Cancer Genome Atlas (TCGA). The corrected description for line 8–10 in abstract is as below: “For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) data depository.” In page 9, the corrected description of list of abbreviations used is as follows: “AUC, Area under curve; BA, Balanced accuracy; BR, Breast cancer; GEO, Gene Expression Omnibus; GO, Gene ontology; HCC, Hepatocellular carcinoma; LC, Lung cancer; LOOCV, Leave-one-out cross-validation; LP, Lymphoma; mRNA, messenger RNA; miRNA, microRNA; PDAC, Pancreatic ductal adenocarcinoma; SVM, Support vector machine;” Author details 1 Interdisciplinary program in Bioinformatics, Seoul National University, Seoul, Korea. 2Department of Statistics, Seoul National University, Seoul, Korea. 3 Department of Mathematics and Statistics, Sejong University, Seoul, Korea. 4 Immunodiagnostics R&D Team, IVD Business Unit, New Business Division, SK telecom Co, Seongnam, Korea. 5Department of Surgery, Seoul National University Hospital, Seoul, Korea. Received: 22 December 2016 Accepted: 22 December 2016
Reference 1. Kwon M-S, et al. Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer. BMC Genomics. 2015;16 Suppl 9:S4. * Correspondence: [email protected]; [email protected] 5 Department of Surgery, Seoul National University Hospital, Seoul, Korea 1 Interdisciplinary program in Bioinformatics, Seoul National University, Seoul, Korea © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
