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      CTR-DB, an omnibus for patient-derived gene expression signatures correlated with cancer drug response

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          Abstract

          To date, only some cancer patients can benefit from chemotherapy and targeted therapy. Drug resistance continues to be a major and challenging problem facing current cancer research. Rapidly accumulated patient-derived clinical transcriptomic data with cancer drug response bring opportunities for exploring molecular determinants of drug response, but meanwhile pose challenges for data management, integration, and reuse. Here we present the Cancer Treatment Response gene signature DataBase (CTR-DB, http://ctrdb.ncpsb.org.cn/), a unique database for basic and clinical researchers to access, integrate, and reuse clinical transcriptomes with cancer drug response. CTR-DB has collected and uniformly reprocessed 83 patient-derived pre-treatment transcriptomic source datasets with manually curated cancer drug response information, involving 28 histological cancer types, 123 drugs, and 5139 patient samples. These data are browsable, searchable, and downloadable. Moreover, CTR-DB supports single-dataset exploration (including differential gene expression, receiver operating characteristic curve, functional enrichment, sensitizing drug search, and tumor microenvironment analyses), and multiple-dataset combination and comparison, as well as biomarker validation function, which provide insights into the drug resistance mechanism, predictive biomarker discovery and validation, drug combination, and resistance mechanism heterogeneity.

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          Most cited references65

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                07 January 2022
                27 September 2021
                27 September 2021
                : 50
                : D1
                : D1184-D1199
                Affiliations
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                Department of Radiation Oncology, China-Japan Friendship Hospital , Beijing 100029, China
                Beijing Geneworks Technology Co., Ltd. , Beijing 100101, China
                Beijing Geneworks Technology Co., Ltd. , Beijing 100101, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                Department of Immunology, Medical College of Qingdao University , Qingdao 266071, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics , Beijing 102206, China
                College of Chemistry and Environmental Science, Hebei University , Baoding 071002, China
                Author notes
                To whom correspondence should be addressed. Tel: +86 106 177 7056; Fax: +86 106 177 7004; Email: liuzy1984@ 123456163.com
                Correspondence may also be addressed to Dong Li. Tel: +86 106 177 7057; Fax: +86 106 177 7004; Email: lidong.bprc@ 123456foxmail.com
                Correspondence may also be addressed to Fuchu He. Tel: +86 106 177 1001; Fax: +86 106 177 7004; Email: hefc@ 123456nic.bmi.ac.cn

                The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

                Author information
                https://orcid.org/0000-0001-7905-3831
                https://orcid.org/0000-0003-4559-5450
                https://orcid.org/0000-0002-2866-4904
                https://orcid.org/0000-0002-8680-0468
                Article
                gkab860
                10.1093/nar/gkab860
                8728209
                34570230
                b5b8d15a-37ad-4bc9-96bf-7e75cf0d51a0
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 15 September 2021
                : 08 September 2021
                : 15 August 2021
                Page count
                Pages: 16
                Funding
                Funded by: National Key Research and Development Program of China, DOI 10.13039/501100012166;
                Award ID: 2020YFE0202200
                Award ID: 2017YFC1700105
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 32088101
                Award ID: 31871341
                Funded by: State Key Laboratory of Proteomics of China;
                Award ID: SKLPO202010
                Funded by: Beijing Talents foundation;
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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