{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:44:10Z","timestamp":1740149050070,"version":"3.37.3"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"S7","license":[{"start":{"date-parts":[[2019,12,1]],"date-time":"2019-12-01T00:00:00Z","timestamp":1575158400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T00:00:00Z","timestamp":1577664000000},"content-version":"vor","delay-in-days":29,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Foundation","award":["1661331"],"award-info":[{"award-number":["1661331"]}]},{"DOI":"10.13039\/100000199","name":"U.S. Department of Agriculture","doi-asserted-by":"crossref","award":["2016-51181-25408"],"award-info":[{"award-number":["2016-51181-25408"]}],"id":[{"id":"10.13039\/100000199","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["U54 CA132383"],"award-info":[{"award-number":["U54 CA132383"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["U54 CA132381"],"award-info":[{"award-number":["U54 CA132381"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Genomics"],"published-print":{"date-parts":[[2019,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n<jats:title>Background<\/jats:title>\n<jats:p>Most statistical methods used to identify cancer driver genes are either biased due to choice of assumed parametric models or insensitive to directional relationships important for causal inference. To overcome modeling biases and directional insensitivity, a recent statistical functional chi-squared test (FunChisq) detects directional association via model-free functional dependency. FunChisq examines patterns pointing from independent to dependent variables arising from linear, non-linear, or many-to-one functional relationships. Meanwhile, the Functional Annotation of Mammalian Genome 5 (FANTOM5) project surveyed gene expression at over 200,000 transcription start sites (TSSs) in nearly all human tissue types, primary cell types, and cancer cell lines. The data cover TSSs originated from both coding and noncoding genes. For the vast uncharacterized human TSSs that may exhibit complex patterns in cancer versus normal tissues, the model-free property of FunChisq provides us an unprecedented opportunity to assess the evidence for a gene\u2019s directional effect on human cancer.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>We first evaluated FunChisq and six other methods using 719 curated cancer genes on the FANTOM5 data. FunChisq performed best in detecting known cancer driver genes from non-cancer genes. We also show the capacity of FunChisq to reveal non-monotonic patterns of functional association, to which typical differential analysis methods such as <jats:italic>t<\/jats:italic>-test are insensitive. Further applying FunChisq to screen unannotated TSSs in FANTOM5, we predicted 1108 putative cancer driver noncoding RNAs, stronger than 90% of curated cancer driver genes. Next, we compared leukemia samples against other samples in FANTOM5 and FunChisq predicted 332\/79 potential biomarkers for lymphoid\/myeloid leukemia, stronger than the TSSs of all 87\/100 known driver genes in lymphoid\/myeloid leukemia.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusions<\/jats:title>\n<jats:p>This study demonstrated the advantage of FunChisq in revealing directional association, especially in detecting non-monotonic patterns. Here, we also provide the most comprehensive catalog of high-quality biomarkers that may play a causative role in human cancers, including putative cancer driver noncoding RNAs and lymphoid\/myeloid leukemia specific biomarkers.<\/jats:p>\n<\/jats:sec>","DOI":"10.1186\/s12920-019-0565-9","type":"journal-article","created":{"date-parts":[[2019,12,30]],"date-time":"2019-12-30T07:02:20Z","timestamp":1577689340000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Directional association test reveals high-quality putative cancer driver biomarkers including noncoding RNAs"],"prefix":"10.1186","volume":"12","author":[{"given":"Hua","family":"Zhong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingzhou","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,12,30]]},"reference":[{"key":"565_CR1","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1186\/1476-4598-10-38","volume":"10","author":"EA Gibb","year":"2011","unstructured":"Gibb EA, Brown CJ, Lam WL. The functional role of long non-coding RNA in human carcinomas. Mol Cancer. 2011; 10:38. https:\/\/doi.org\/10.1186\/1476-4598-10-38.","journal-title":"Mol Cancer"},{"issue":"11","key":"565_CR2","doi-asserted-by":"publisher","first-page":"582","DOI":"10.5732\/cjc.013.10170","volume":"32","author":"T Huang","year":"2013","unstructured":"Huang T, Alvarez A, Hu B, Cheng S-Y. Noncoding RNAs in cancer and cancer stem cells. Chin J Cancer. 2013; 32(11):582\u201393. https:\/\/doi.org\/10.5732\/cjc.013.10170.","journal-title":"Chin J Cancer"},{"issue":"1","key":"565_CR3","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/jhg.2016.66","volume":"62","author":"Y Kita","year":"2017","unstructured":"Kita Y, Yonemori K, Osako Y, Baba K, Mori S, Maemura K, Natsugoe S. Noncoding RNA and colorectal cancer: its epigenetic role. J Hum Genet. 2017; 62(1):41\u20137. https:\/\/doi.org\/10.1038\/jhg.2016.66.","journal-title":"J Hum Genet"},{"issue":"1A","key":"565_CR4","doi-asserted-by":"publisher","first-page":"68","DOI":"10.5114\/wo.2014.47136","volume":"19","author":"K Tomczak","year":"2015","unstructured":"Tomczak K, Czerwi\u0144ska P, Wiznerowicz M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp Oncol. 2015; 19(1A):68\u201377. https:\/\/doi.org\/10.5114\/wo.2014.47136.","journal-title":"Contemp Oncol"},{"key":"565_CR5","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1186\/s13059-014-0560-6","volume":"16","author":"M Lizio","year":"2015","unstructured":"Lizio M, Harshbarger J, Shimoji H, Severin J, Kasukawa T, Sahin S, Abugessaisa I, Fukuda S, Hori F, Ishikawa-Kato S, Mungall CJ, Arner E, Baillie JK, Bertin N, Bono H, de Hoon M, Diehl AD, Dimont E, Freeman TC, Fujieda K, Hide W, Kaliyaperumal R, Katayama T, Lassmann T, Meehan TF, Nishikata K, Ono H, Rehli M, Sandelin A, Schultes EA, \u2019t Hoen PAC, Tatum Z, Thompson M, Toyoda T, Wright DW, Daub CO, Itoh M, Carninci P, Hayashizaki Y, Forrest ARR, Kawaji H. Gateways to the fantom5 promoter level mammalian expression atlas. Genome Biol. 2015; 16:22. https:\/\/doi.org\/10.1186\/s13059-014-0560-6.","journal-title":"Genome Biol"},{"issue":"8","key":"565_CR6","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1093\/bioinformatics\/btu811","volume":"31","author":"X-M Zhao","year":"2015","unstructured":"Zhao X-M, Liu K-Q, Zhu G, He F, Duval B, Richer J-M, Huang D-S, Jiang C-J, Hao J-K, Chen L. Identifying cancer-related microRNAs based on gene expression data. Bioinformatics. 2015; 31(8):1226\u201334. https:\/\/doi.org\/10.1093\/bioinformatics\/btu811.","journal-title":"Bioinformatics"},{"key":"565_CR7","doi-asserted-by":"publisher","first-page":"16025","DOI":"10.1038\/celldisc.2016.25","volume":"2","author":"J-H Lee","year":"2016","unstructured":"Lee J-H, Zhao X-M, Yoon I, Lee JY, Kwon NH, Wang Y-Y, Lee K-M, Lee M-J, Kim J, Moon H-G, In Y, Hao J-K, Park K-M, Noh D-Y, Han W, Kim S. Integrative analysis of mutational and transcriptional profiles reveals driver mutations of metastatic breast cancers. Cell Discov. 2016; 2:16025. https:\/\/doi.org\/10.1038\/celldisc.2016.25.","journal-title":"Cell Discov"},{"key":"565_CR8","unstructured":"Zhang Y, Song M. Deciphering interactions in causal networks without parametric assumptions. arXiv Mol Netw. 2013:1311\u20132707. http:\/\/arxiv.org\/abs\/1311.2707."},{"issue":"3","key":"565_CR9","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1109\/TCBB.2018.2809743","volume":"16","author":"H Zhong","year":"2019","unstructured":"Zhong H, Song M. A fast exact functional test for directional association and cancer biology applications. IEEE\/ACM Trans Comput Biol Bioinforma. 2019; 16(3):818\u201326. https:\/\/doi.org\/10.1109\/TCBB.2018.2809743.","journal-title":"IEEE\/ACM Trans Comput Biol Bioinforma"},{"key":"565_CR10","unstructured":"Zhang Y, Zhong H, Sharma R, Kumar S, Song J. FunChisq: Chi-Square and Exact Tests for Model-Free Functional Dependency. 2018. R package version 2.4.5-3. https:\/\/CRAN.R-project.org\/package=FunChisq. Accessed 6 Dec 2018."},{"issue":"4","key":"565_CR11","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1038\/nmeth.3773","volume":"13","author":"SM Hill","year":"2016","unstructured":"Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Lee WS, Taylor D, Hu CW, Long BL, Noren DP, Bisberg AJ, The HPN-DREAM Consortium, Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez-Rodriguez J, Mukherjee S. Inferring causal molecular networks: empirical assessment through a community-based effort. Nat Methods. 2016; 13(4):310\u20138. https:\/\/doi.org\/10.1038\/nmeth.3773.","journal-title":"Nat Methods"},{"issue":"302","key":"565_CR12","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1080\/14786440009463897","volume":"50","author":"K Pearson","year":"1900","unstructured":"Pearson K. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philos Mag Ser 5. 1900; 50(302):157\u201375.","journal-title":"Philos Mag Ser 5"},{"issue":"6","key":"565_CR13","doi-asserted-by":"publisher","first-page":"80","DOI":"10.2307\/3001968","volume":"1","author":"F Wilcoxon","year":"1945","unstructured":"Wilcoxon F. Individual comparisons by ranking methods. Biom Bull. 1945; 1(6):80\u20133.","journal-title":"Biom Bull"},{"key":"565_CR14","volume-title":"Mathematical Statistics and Data Analysis, 3rd edn.","author":"J Rice","year":"2006","unstructured":"Rice J. Mathematical Statistics and Data Analysis, 3rd edn.Belmont: Thomas Higher Education; 2006."},{"key":"565_CR15","doi-asserted-by":"publisher","DOI":"10.1002\/9781118548387","volume-title":"Applied Logistic Regression vol. 398, 3rd edn.","author":"DW Hosmer Jr","year":"2013","unstructured":"Hosmer Jr DW, Lemeshow S, Sturdivant RX. Applied Logistic Regression vol. 398, 3rd edn.Hoboken: John Wiley & Sons; 2013."},{"issue":"12","key":"565_CR16","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1186\/s13059-014-0550-8","volume":"15","author":"MI Love","year":"2014","unstructured":"Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12):550.","journal-title":"Genome Biol"},{"issue":"1","key":"565_CR17","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","volume":"26","author":"MD Robinson","year":"2010","unstructured":"Robinson MD, McCarthy DJ, Smyth GK. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010; 26(1):139\u201340.","journal-title":"Bioinformatics"},{"issue":"3","key":"565_CR18","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1038\/nrc1299","volume":"4","author":"PA Futreal","year":"2004","unstructured":"Futreal PA, Coin L, Marshall M, Down T, Hubbard T, Wooster R, Rahman N, Stratton MR. A census of human cancer genes. Nat Rev Cancer. 2004; 4(3):177\u201383.","journal-title":"Nat Rev Cancer"},{"issue":"2","key":"565_CR19","doi-asserted-by":"publisher","first-page":"29","DOI":"10.32614\/RJ-2011-015","volume":"3","author":"H Wang","year":"2011","unstructured":"Wang H, Song M. Ckmeans.1d.dp: Optimal k-means clustering in one dimension by dynamic programming. R J. 2011; 3(2):29\u201333. https:\/\/doi.org\/10.32614\/RJ-2011-015.","journal-title":"R J"},{"key":"565_CR20","unstructured":"Song J, Wang H. Ckmeans.1d.dp: Optimal and Fast Univariate Clustering. 2018. R package version 4.2.2. https:\/\/cran.r-project.org\/package=Ckmeans.1d.dp. Accessed 1 Dec 2018."},{"issue":"1","key":"565_CR21","doi-asserted-by":"publisher","first-page":"289","DOI":"10.32614\/RJ-2016-021","volume":"8","author":"L Scrucca","year":"2016","unstructured":"Scrucca L, Fop M, Murphy TB, Raftery AE. mclust 5: Clustering, classification and density estimation using Gaussian finite mixture models. R J. 2016; 8(1):289\u2013317. https:\/\/doi.org\/10.32614\/RJ-2016-021.","journal-title":"R J"},{"issue":"22","key":"565_CR22","doi-asserted-by":"publisher","first-page":"6190","DOI":"10.1158\/0008-5472.CAN-17-1388","volume":"77","author":"D Lv","year":"2017","unstructured":"Lv D, Jia F, Hou Y, Sang Y, Alvarez AA, Zhang W, Gao W-Q, Hu B, Cheng S-Y, Ge J, Li Y, Feng H. Histone acetyltransferase KAT6A upregulates PI3K\/Akt signaling through TRIM24 binding. Cancer Res. 2017; 77(22):6190\u2013201. https:\/\/doi.org\/10.1158\/0008-5472.CAN-17-1388.","journal-title":"Cancer Res"},{"issue":"1","key":"565_CR23","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.critrevonc.2012.11.003","volume":"87","author":"F Sclafani","year":"2013","unstructured":"Sclafani F, Gullo G, Sheahan K, Crown J. Braf mutations in melanoma and colorectal cancer: a single oncogenic mutation with different tumour phenotypes and clinical implications. Crit Rev Oncol Hematol. 2013; 87(1):55\u201368.","journal-title":"Crit Rev Oncol Hematol"},{"issue":"47","key":"565_CR24","doi-asserted-by":"publisher","first-page":"5807","DOI":"10.1038\/onc.2015.33","volume":"34","author":"BN Sheikh","year":"2015","unstructured":"Sheikh BN, Phipson B, El-Saafin F, Vanyai HK, Downer NL, Bird MJ, Kueh AJ, May RE, Smyth GK, Voss AK, Thomas T. MOZ (MYST3, KAT6A) inhibits senescence via the INK4A-ARF pathway. Oncogene. 2015; 34(47):5807\u201320. https:\/\/doi.org\/10.1038\/onc.2015.33.","journal-title":"Oncogene"},{"issue":"22","key":"565_CR25","doi-asserted-by":"publisher","first-page":"8659","DOI":"10.1073\/pnas.83.22.8659","volume":"83","author":"W O\u2019Brien","year":"1986","unstructured":"O\u2019Brien W, Stenman G, Sager R. Suppression of tumor growth by senescence in virally transformed human fibroblasts. Proc Natl Acad Sci U S A. 1986; 83(22):8659\u201363.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"3","key":"565_CR26","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/S1535-6108(03)00051-5","volume":"3","author":"K Deguchi","year":"2003","unstructured":"Deguchi K, Ayton PM, Carapeti M, Kutok JL, Snyder CS, Williams IR, Cross NC, Glass CK, Cleary ML, Gilliland DG. MOZ-TIF2-induced acute myeloid leukemia requires the MOZ nucleosome binding motif and TIF2-mediated recruitment of CBP. Cancer Cell. 2003; 3(3):259\u201371.","journal-title":"Cancer Cell"},{"issue":"5","key":"565_CR27","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1038\/nm.2122","volume":"16","author":"Y Aikawa","year":"2010","unstructured":"Aikawa Y, Katsumoto T, Zhang P, Shima H, Shino M, Terui K, Ito E, Ohno H, Stanley ER, Singh H, Tenen DG, Kitabayashi I. PU,1-mediated upregulation of CSF1R is crucial for leukemia stem cell potential induced by MOZ-TIF2. Nat Med. 2010; 16(5):580\u20135. https:\/\/doi.org\/10.1038\/nm.2122.","journal-title":"Nat Med"},{"issue":"8","key":"565_CR28","doi-asserted-by":"publisher","first-page":"3130","DOI":"10.1182\/blood.V90.8.3130","volume":"90","author":"RC Aguiar","year":"1997","unstructured":"Aguiar RC, Chase A, Coulthard S, Macdonald DH, Carapeti M, Reiter A, Sohal J, Lennard A, Goldman JM, Cross NC. Abnormalities of chromosome band 8p11 in leukemia: two clinical syndromes can be distinguished on the basis of moz involvement. Blood. 1997; 90(8):3130\u20135.","journal-title":"Blood"},{"issue":"1","key":"565_CR29","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/ng0996-33","volume":"14","author":"J Borrow","year":"1996","unstructured":"Borrow J, Stanton VPJ, Andresen JM, Becher R, Behm FG, Chaganti RS, Civin CI, Disteche C, Dube I, Frischauf AM, Horsman D, Mitelman F, Volinia S, Watmore AE, Housman DE. The translocation t(8;16)(p11;p13) of acute myeloid leukaemia fuses a putative acetyltransferase to the CREB-binding protein. Nat Genet. 1996; 14(1):33\u201341. https:\/\/doi.org\/10.1038\/ng0996-33.","journal-title":"Nat Genet"},{"issue":"20","key":"565_CR30","doi-asserted-by":"publisher","first-page":"2910","DOI":"10.1038\/onc.2016.433","volume":"36","author":"L Yu","year":"2017","unstructured":"Yu L, Liang Y, Cao X, Wang X, Gao H, Lin S-Y, Schiff R, Wang X-S, Li K. Identification of MYST3 as a novel epigenetic activator of ER \u03b1 frequently amplified in breast cancer. Oncogene. 2017; 36(20):2910.","journal-title":"Oncogene"},{"key":"565_CR31","doi-asserted-by":"publisher","first-page":"38988","DOI":"10.1038\/srep38988","volume":"6","author":"Z Waks","year":"2016","unstructured":"Waks Z, Weissbrod O, Carmeli B, Norel R, Utro F, Goldschmidt Y. Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins. Sci Rep. 2016; 6:38988.","journal-title":"Sci Rep"},{"key":"565_CR32","first-page":"1657","volume":"7","author":"A Eych\u00e8ne","year":"1992","unstructured":"Eych\u00e8ne A, Vianney-Barnier J, Apiou F, Dutrillaux B, Calothy G. Chromosomal assignment of two human B-raf (Rmil) proto-oncogene loci: B-raf-1 encoding the p94Braf\/Rmil and B-raf-2, a processed pseudogene. Oncogene. 1992; 7:1657\u201360.","journal-title":"Oncogene"},{"issue":"13","key":"565_CR33","doi-asserted-by":"publisher","first-page":"3833","DOI":"10.1016\/j.celrep.2017.11.104","volume":"21","author":"K Tong","year":"2017","unstructured":"Tong K, Pellon-Cardenas O, Sirihorachai VR, Warder BN, Kothari OA, Perekatt AO, Fokas EE, Fullem RL, Zhou A, Thackray JK, Tran H, Zhang L, Xing J, Verzi MP. Degree of tissue differentiation dictates susceptibility to BRAF-driven colorectal cancer. Cell Rep. 2017; 21(13):3833\u201345. https:\/\/doi.org\/10.1016\/j.celrep.2017.11.104.","journal-title":"Cell Rep"},{"key":"565_CR34","doi-asserted-by":"publisher","first-page":"435983","DOI":"10.1155\/2014\/435983","volume":"2014","author":"A Puiggros","year":"2014","unstructured":"Puiggros A, Blanco G, Espinet B. Genetic abnormalities in chronic lymphocytic leukemia: where we are and where we go. BioMed Res Int. 2014; 2014:435983.","journal-title":"BioMed Res Int"},{"issue":"1","key":"565_CR35","doi-asserted-by":"publisher","first-page":"77","DOI":"10.4274\/tjh.2013.0107","volume":"32","author":"M Gupta","year":"2015","unstructured":"Gupta M, Radhakrishnan N, Mahapatra M, Saxena R. Trisomy chromosome 6 as a sole cytogenetic abnormality in acute myeloid leukemia. Turk J Haematol. 2015; 32(1):77\u20139. https:\/\/doi.org\/10.4274\/tjh.2013.0119.","journal-title":"Turk J Haematol"},{"issue":"10","key":"565_CR36","doi-asserted-by":"publisher","first-page":"3838","DOI":"10.1182\/blood-2002-07-2225","volume":"100","author":"SD Nimer","year":"2002","unstructured":"Nimer SD, MacGrogan D, Jhanwar S, Alvarez S. Chromosome 19 abnormalities are commonly seen in AML, M7. Blood. 2002; 100(10):3838.","journal-title":"Blood"},{"issue":"4","key":"565_CR37","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1086\/288105","volume":"33","author":"HA Simon","year":"1966","unstructured":"Simon HA, Rescher N. Cause and counterfactual. Philos Sci. 1966; 33(4):323\u201340.","journal-title":"Philos Sci"},{"key":"565_CR38","volume-title":"Statistics for Experimenters: Design, Innovation, and Discovery 2nd edn.","author":"GE Box","year":"2005","unstructured":"Box GE, Hunter JS, Hunter WG. Statistics for Experimenters: Design, Innovation, and Discovery 2nd edn.New York: Wiley-Interscience; 2005."}],"container-title":["BMC Medical Genomics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12920-019-0565-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12920-019-0565-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12920-019-0565-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T00:08:58Z","timestamp":1609200538000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedgenomics.biomedcentral.com\/articles\/10.1186\/s12920-019-0565-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12]]},"references-count":38,"journal-issue":{"issue":"S7","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["565"],"URL":"https:\/\/doi.org\/10.1186\/s12920-019-0565-9","relation":{},"ISSN":["1755-8794"],"issn-type":[{"type":"electronic","value":"1755-8794"}],"subject":[],"published":{"date-parts":[[2019,12]]},"assertion":[{"value":"18 July 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This article has been published as part of <i>BMC Medical Genomics<\/i>, Volume 12 Supplement 7, 2019: Selected articles from the 14th International Symposium on Bioinformatics Research and Applications (ISBRA-18): medical genomics. The full contents of the supplement are available at v","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"About this supplement"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"129"}}