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The Cancer Omics Atlas: an integrative resource for cancer omics annotations
BACKGROUND: The Cancer Genome Atlas (TCGA) is an important data resource for cancer biologists and oncologists. However, a lack of bioinformatics expertise often hinders experimental cancer biologists and oncologists from exploring the TCGA resource. Although a number of tools have been developed fo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6083503/ https://www.ncbi.nlm.nih.gov/pubmed/30089500 http://dx.doi.org/10.1186/s12920-018-0381-7 |
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author | Sun, Qingrong Li, Mengyuan Wang, Xiaosheng |
author_facet | Sun, Qingrong Li, Mengyuan Wang, Xiaosheng |
author_sort | Sun, Qingrong |
collection | PubMed |
description | BACKGROUND: The Cancer Genome Atlas (TCGA) is an important data resource for cancer biologists and oncologists. However, a lack of bioinformatics expertise often hinders experimental cancer biologists and oncologists from exploring the TCGA resource. Although a number of tools have been developed for facilitating cancer researchers to utilize the TCGA data, these existing tools cannot fully satisfy the large community of experimental cancer biologists and oncologists without bioinformatics expertise. METHODS: We developed a new web-based tool The Cancer Omics Atlas (TCOA, http://tcoa.cpu.edu.cn) for fast and straightforward querying of TCGA “omics” data. RESULTS: TCOA provides the querying of gene expression, somatic mutations, microRNA (miRNA) expression, protein expression data based on a single molecule or cancer type. TCOA also provides the querying of expression correlation between gene pairs, miRNA pairs, gene and miRNA, and gene and protein. Moreover, TCOA provides the querying of the associations between gene, miRNA, or protein expression and survival prognosis in cancers. In addition, TCOA displays transcriptional profiles across various human cancer types based on the pan-cancer analysis. Finally, TCOA provides the querying of molecular profiles for 2877 immune-related genes in human cancers. These immune-related genes include those that are established or promising targets for cancer immunotherapy such as CTLA4, PD1, PD-L1, PD-L2, IDO1, LAG3, and TIGIT. CONCLUSIONS: TCOA is a useful tool that supplies a number of unique and new functions complementary to the existing tools to facilitate exploration of the TCGA resource. |
format | Online Article Text |
id | pubmed-6083503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60835032018-08-10 The Cancer Omics Atlas: an integrative resource for cancer omics annotations Sun, Qingrong Li, Mengyuan Wang, Xiaosheng BMC Med Genomics Database BACKGROUND: The Cancer Genome Atlas (TCGA) is an important data resource for cancer biologists and oncologists. However, a lack of bioinformatics expertise often hinders experimental cancer biologists and oncologists from exploring the TCGA resource. Although a number of tools have been developed for facilitating cancer researchers to utilize the TCGA data, these existing tools cannot fully satisfy the large community of experimental cancer biologists and oncologists without bioinformatics expertise. METHODS: We developed a new web-based tool The Cancer Omics Atlas (TCOA, http://tcoa.cpu.edu.cn) for fast and straightforward querying of TCGA “omics” data. RESULTS: TCOA provides the querying of gene expression, somatic mutations, microRNA (miRNA) expression, protein expression data based on a single molecule or cancer type. TCOA also provides the querying of expression correlation between gene pairs, miRNA pairs, gene and miRNA, and gene and protein. Moreover, TCOA provides the querying of the associations between gene, miRNA, or protein expression and survival prognosis in cancers. In addition, TCOA displays transcriptional profiles across various human cancer types based on the pan-cancer analysis. Finally, TCOA provides the querying of molecular profiles for 2877 immune-related genes in human cancers. These immune-related genes include those that are established or promising targets for cancer immunotherapy such as CTLA4, PD1, PD-L1, PD-L2, IDO1, LAG3, and TIGIT. CONCLUSIONS: TCOA is a useful tool that supplies a number of unique and new functions complementary to the existing tools to facilitate exploration of the TCGA resource. BioMed Central 2018-08-08 /pmc/articles/PMC6083503/ /pubmed/30089500 http://dx.doi.org/10.1186/s12920-018-0381-7 Text en © The Author(s). 2018 Open AccessThis 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. |
spellingShingle | Database Sun, Qingrong Li, Mengyuan Wang, Xiaosheng The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title | The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title_full | The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title_fullStr | The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title_full_unstemmed | The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title_short | The Cancer Omics Atlas: an integrative resource for cancer omics annotations |
title_sort | cancer omics atlas: an integrative resource for cancer omics annotations |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6083503/ https://www.ncbi.nlm.nih.gov/pubmed/30089500 http://dx.doi.org/10.1186/s12920-018-0381-7 |
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