dataesr/scientific-paragraphs-categorization huggingface dataset:
2011) , J-band observations from VHS and VIKING will be used. Reed et al. (2015)  illustrated the promise of quasar discovery with DES with the discovery of a quasar at z > 6. The quasar was the brightest of 43 candidates and was identified for follow-up work solely on the DES i -z and z -Y colours. Spectroscopy of the quasar, DES J0454-4448, showed that it has an emission redshift of z = 6. 10 ± 0. 03 and an H I near zone size of 4. 6 ± 1. 7 Mpc. The presence of one z > 6 quasar in the relatively small area probed by the DES SV data is consistent with the luminosity function expected at z ∼ 6. Quasars at redshifts below six show a substantial amount of Lyman α absorption due to intervening neutral hydrogen gas at lower redshift, yet the transmission of some quasar continuum below the break indicates that the IGM is mostly ionized.
Data from DES can help to address both of these issues. DES data will allow us to resolve low surface brightness features far from the quasar nuclear flux. A census of merging systems in non-quasar hosts over the same redshift range can also be extracted from the DES data and used as a control sample. This control sample is important to quantify the fraction of all mergers that are detectable at the larger radii probed by quasar hosts. Fig. 14  shows the difference between the point spread function (PSF) and model magnitude in the i band for a sample of known luminous quasars overlapping DES SV data from Veron-Cetty & Veron (1993). As the PSF magnitude only encompasses flux in the central nuclear region whereas the model magnitude is a better measure of the total flux, unresolved point sources will have a small difference between their PSF and model magnitudes whereas extended sources will have a much larger difference.
The DES Data Management system is supported by the  National Science Foundation  under Grant Number  AST-1138766. The Collaborating Institutions are  Argonne National Laboratory , the  University of California at Santa Cruz , the  University of Cambridge, Centro de Investigaciones Enérgeticas ,  Medioambientales y Tecnológicas-Madrid , the  University of Chicago ,  University College London , the  DES-Brazil Consortium , the  University of Edinburgh , the  Eidgenössische Technische Hochschule (ETH) Zürich ,  Fermi National Accelerator Laboratory , the  University of Illinois at Urbana-Champaign , the  Institut de Ciències de l'Espai (IEEC/CSIC) , the  Institut de Física d'Altes Energies ,  Lawrence Berkeley National Laboratory , the  Ludwig-Maximilians Universität München  and the associated  Excellence Cluster Universe , the  University of Michigan , the  National Optical Astronomy Observatory , the  University of Nottingham , the  Ohio State University , the  University of Pennsylvania , the  University of Portsmouth ,  SLAC National Accelerator Laboratory ,  Stanford University , the  University of Sussex  and  Texas A&M University.
OL acknowledges support from a  European Research Council Advanced  Grant  FP7/291329. The DES participants from Spanish institutions are partially supported by  MINECO  under grants  AYA2012-39559 ,  ESP2013-48274 ,  FPA2013-47986  and  Centro de Excelencia Severo Ochoa   SEV-2012-0234. Research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Programme  (FP7/2007-2013) including  ERC  grant agreements  240672 ,  291329  and  306478. We are grateful for the extraordinary contributions of our CTIO colleagues and the  DECam Construction, Commissioning and Science Verification  teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DES Data Management group.
As part of the Collaborative Oncological Gene-Environment Study (COGS), we conducted a comprehensive fine-scale mapping of this 17q22 breast cancer susceptibility locus using 517 SNPs chosen to give dense coverage across this locus. These were genotyped on a custom-designed Illumina iSelect genotyping array (iCOGS) in 50 studies participating in BCAC. We used these data to define the variants most strongly associated with risk, and combined these data with additional in-silico and functional data in an attempt to determine the most likely causal variants.
We performed iCOGS genotyping in four centres, as part of the Collaborative Oncological Gene-Environment Study (COGS). All BCAC studies had local human ethical approvals as described previously  8. We then used the genotype data from 517 SNPs that passed quality control to impute genotypes, among European subjects, at all additional known variants in the interval, using IMPUTE version 2. 0 (IMPUTE2; without pre-phasing) and the 1000 genome project multi-population data (March 2012 version) as a reference panel  9, 10. IMPUTE2 was run with default parameters and "effective size" of the population Ne = 20,000. Using an imputation-r 2 > 0. 3 in Europeans, we successfully imputed 3,134 SNPs (MAF ≥ 1%). differences as previously described  8. For the analyses of European subjects, we included the first six principal components as covariates, together with a seventh component derived specifically for one study (LMBC) for which there was substantial inflation not accounted for by the components derived from the analysis of all studies (this component was set to zero for all other studies).
Bioinformatic analyses. We combined multiple sources of in silico annotation from public databases to help identify potential functional SNPs. To investigate functional elements enriched across the previously defined fine-mapped region, more specifically in the region encompassing the strongest candidate causal SNPs, we analysed chromatin biofeatures data from the Encyclopedia of DNA Elements (ENCODE) Project 14 namely: Chromatin State Segmentation by Hidden Markov Models (chromHMM), DNase I hypersensitivity sites (DHS) and histone modifications of epigenetic markers H3K4, H3K9, and H3K27 in Human Mammary Epithelial Cells (HMEC) and MCF7 breast cancer cells. To identify putative target genes, we examined chromatin interactions between distal and proximal regulatory transcription-factor binding sites and gene promoters, using Chromatin Interaction Analysis by Paired End Tag (ChiA-PET) in MCF7 cells.
This detects genome-wide interactions associated with CCCTC-binding factor (CTCF) and DNA polymerase II (Pol2) -both involved in transcriptional regulation  15. Putative regulatory elements were determined using data from ENCODE, Roadmap Epigenomics  16  , the "Predicting Specific Tissue Interactions of Genes and Enhancers" (PreSTIGE)  17  algorithm, Hnisz  18  and FANTOM. Intersections between candidate causal variants and regulatory elements were identified using Galaxy, and visualised in the UCSC Genome Browser. We used the ENCODE RNAseq data to evaluate the expression of exons across the 17q22 locus in HMEC and MCF7 cell lines. The alignment files for HMEC (4 biological replicates) and MCF7 (19 biological replicates) were downloaded from ENCODE and the read count in the defined region was extracted and normalized in reads per million (RPM).
Allele specific expression (ASE) analysis. ASE analysis was performed using The Cancer Genome Atlas (TCGA) breast cancer data as described previously  19. SNP rs2787481, genotyped on the Affymetrix SNP Array 6. 0 was used as a representative SNP for the candidate causal variants (r 2 = 0. 90 with rs2787486). SNP rs2787481 genotype calls and the corresponding confidence scores were retrieved using level 2 TCGA SNP array Birdseed data downloaded from TCGA portal. Genotypes with confidence scores equal to or above 0. 1 were excluded. We utilised RNA-sequencing data from 742 breast cancer samples from women of Caucasian ancestry. The corresponding RNA-sequencing BAM files and metadata are available from the Cancer Genomics Hub (CGHub). Markers used to assess relative allelic expression were exonic SNPs located in KIF2B, TOM1L1, COX11, STXBP4, HLF, MMD, TMEM100, PCTP, and ANKFN1 extracted from dbSNP human Build 142.
Homozygote marker SNPs, those with low coverage (less than 15x) and those within overlapping regions of the target genes, were removed. RNA-sequencing read counts on SNP sites for reference and alternative alleles were computed. The major allele fraction (μ ), representing allelic imbalance for each marker SNP, was computed and an average of allelic imbalances for each gene was calculated for individual tumour samples. Marker SNPs with extreme μ values (μ > 0. 75) were not included in the analysis. Level 3 SNP array data were downloaded from TCGA portal and GISTIC version 2. 0. 16 was used to identify copy number variations (CNVs) for each sample. Samples with low or high CNV levels, as presented in the gene-based GISTIC module report, were excluded from the analysis of the corresponding gene.
Local gene expression by SNP (eQTL) association analysis. We examined the association of all genotyped or imputed SNPs with expression of nine genes (KIF2B, TOM1L1, COX11, STXBP4, HLF, MMD, TMEM100, PCTP, and ANKFN1) in the 1 Mb region on either side of the fine-mapping interval, using data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) study. METABRIC comprises normal tissues adjacent to tumours from breast cancer patients genetically confirmed to be of European ancestry  20. The samples (n = 135) were assayed for expression with the Illumina HT-12 v3 microarray. Matched germline SNP genotypes were derived using the Affymetrix SNP 6. 0 array. Genotyping quality control and imputation for the METABRIC data are described in Guo et al. 21. Association between genotype and expression was tested by linear regression with FDR control as implemented in the MatrixEQTL  22  package in R  11.
Unexpressed and minimally expressed genes/isoforms whose sum in expression level was less than ten were excluded, and the data log2 transformed prior to analysis. The influence of SNPs on local gene expression (transcripts within 1 MB from the most strongly associated SNP) was assessed using a linear regression model, as implemented in the R 11 library eMAP  26. An additive effect was assumed by modelling the patient's number of copies of the rare allele, i. e. 0, 1 or 2 for a given genotype. Correction for multiple testing was performed using the false discovery rate (FDR) as implemented in the p. adjust function in R. eQTL data from the Genotype-Tissue Expression (GTEx) project  27  were downloaded from the v6 release.
Teresa Selander, Nayana Weerasooriya; ORIGO: We thank E. Krol-Warmerdam, and J. Blom for patient accrual, administering questionnaires, and managing clinical information. The LUMC survival data were retrieved from the Leiden hospital-based cancer registry system (ONCDOC) with the help of Dr. J. Molenaar; PBCS: Louise Brinton, Mark Sherman, Neonila Szeszenia-Dabrowska, Beata Peplonska, Witold Zatonski, Pei Chao, Michael Stagner; pKARMA: The Swedish Medical Research Counsel; RBCS: Petra Bos, Jannet Blom, Ellen Crepin,.
Acknowledgements The authors thank all the individuals who took part in these studies and all the researchers, study staff, clinicians, and other healthcare providers, technicians, and administrative staff who have enabled this work to be carried out. In particular, they thank: COGS:  Andrew Berchuck  (OCAC),  Rosalind A. Eeles ,  Ali Amin Al Olama ,  Zsofia Kote-Jarai ,  Sara Benlloch  (PRACTICAL),  Antonis Antoniou ,  Lesley McGuffog  and  Ken Offit  (CIMBA),  Joe Dennis ,  Andrew Lee , and  Ed Dicks ,  Craig Luccarini  and the staff of the  Centre for Genetic Epidemiology Laboratory  and the staff of the CNIO genotyping unit,  Francois Bacot ,  Sylvie LaBoissière  and  Frederic Robidoux  and the staff of the  McGill University and Genome Quebec Innovation Centre ,  Sune F. Nielsen ,  Borge G.
For the excellent technical assistance:  Dorthe Uldall Andersen ,  Maria Birna Arnadottir ,  Anne Bank ,  Dorthe Kjeldgård Hansen. The  Danish Cancer Biobank  is acknowledged for providing infrastructure for the collection of blood samples for the cases; CNIO-BCS:  Charo Alonso ,  Daniel for the Third Term Comprehensive 10-Year Strategy for Cancer Control  from  Ministry Health, Labour and Welfare of Japan , by  Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan , by  National Cancer Center Research and Development Fund, and "Practical Research for Innovative Cancer Control  ( 15ck0106177h0001 )" from  Japan Agency for Medical Research and development, AMED , and  Cancer Bio Bank Aichi ; HMBCS: The HMBCS was supported by a grant from the  Friends of Hannover Medical School  and by the  Rudolf Bartling Foundation ; KARBAC: Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between  Stockholm County Council and Karolinska Institutet , the  Swedish Cancer Society , The Gustav V Jubilee foundation and Bert von Kantzows foundation; KBCP: The KBCP was financially supported by the special Government Funding (EVO) of  Kuopio University Hospital  grants,  Cancer Fund of North Savo , the  Finnish Cancer Organizations , and by the strategic funding of the  University of Eastern Finland ; kConFab/AOCS: kConFab is supported by a grant from the  National Breast Cancer Foundation , and previously by the  National Health and Medical Research Council (NHMRC) , the  Queensland Cancer Fund , the  Cancer Councils of New South Wales, Victoria , Tasmania and  South Australia , and the  Cancer Foundation of Western Australia.
Financial support for the AOCS was provided by the  United States Army Medical Research and Materiel Command  [ DAMD17-01-1-0729 ],  Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia , The  Cancer Foundation of Western Australia, Cancer Council Tasmania  and the  National Health and Medical Research Council of Australia  (NHMRC; 400413, 400281, 199600). G. C. T. and P. W. are supported by the  NHMRC. RB was a  Cancer Institute NSW Clinical  Research Fellow; LAABC: LAABC is supported by grants ( 1RB-0287 ,  3PB-0102 ,  5PB-0018 ,  10PB-0098 ) from the  California Breast Cancer Research Program. Incident breast cancer cases were collected by the  USC Cancer Surveillance Program (CSP)  which is supported under subcontract by the  California Department of Health.
and Margaret T. Grohne Family Foundation  and the  Ting Tsung and Wei Fong Chao Foundation ; MCCS: MCCS cohort recruitment was funded by  VicHealth  and  Cancer Council Victoria. The MCCS was further supported by Australian  NHMRC  grants  209057 ,  251553  and  504711  and by infrastructure provided by  Cancer Council Victoria. Cases and their vital status were ascertained through the  Victorian Cancer Registry (VCR)  and the  Australian Institute of Health and Welfare (AIHW) , including the  National Death Index  and the Australian Cancer Database; MEC: The MEC was support by  NIH  grants  CA63464 ,  CA54281 ,  CA098758  and  CA132839 ; MTLGEBCS: The work of MTLGEBCS was supported by the  Quebec Breast Cancer Foundation , the  Canadian Institutes of Health Research for the "CIHR Team in Familial Risks of Breast Cancer" program  -grant #  CRN-87521  and the  Ministry of Economic Development, Innovation and Export Trade  -grant #  PSR-SIIRI-701 ; MYBRCA: MYBRCA is funded by research grants from the  Malaysian Ministry of Science, Technology and Innovation (MOSTI) ,  Malaysian Ministry of Higher Education  ( UM.
Biological sample preparation was conducted the  Survey and Biospecimen Shared Resource , which is supported by  P30 CA68485 ; OBCS: The OBCS was supported by research grants from the  Finnish Cancer Foundation , the  Academy of Finland  (grant number  250083 ,  122715  and  Center of Excellence  grant number  251314 ), the  Finnish Cancer Foundation , the  Sigrid Juselius Foundation , the  University of Oulu , the  University of Oulu Support Foundation  and the special Governmental EVO funds for Oulu University Hospitalbased research activities; OFBCR: The  Ontario Familial Breast Cancer Registry (OFBCR)  was supported by grant  UM1 CA164920  from the  National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the  National Cancer Institute  or any of the collaborating centers in the  Breast Cancer Family Registry (BCFR) , nor does mention of trade names, commercial products, or organizations imply endorsement by the  USA Government  or the BCFR; ORIGO: The ORIGO study was supported by the  Dutch Cancer Society  ( RUL 1997-1505 ) and the  Biobanking and Biomolecular Resources Research Infrastructure  ( BBMRI-NL CP16 ); PBCS: The PBCS was funded by  Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA ; pKARMA: The pKARMA study was supported by  Märit and Hans Rausings Initiative Against Breast Cancer ; RBCS:The RBCS was funded by the  Dutch Cancer Society  ( DDHK 2004-3124 ,  DDHK 2009-4318 ); SASBAC: The SASBAC study was supported by funding from the  Agency for Science, Technology and Research of Singapore (A*STAR) , the  US National Institute of Health (NIH)  and the  Susan G.
UKBGS: We thank  Breast Cancer Now  and the  Institute of Cancer Research for support and funding of the Breakthrough Generations Study , and the study participants, study staff, and the doctors, nurses and other health care providers and health information sources who have contributed to the study. We acknowledge NHS funding to the  Royal Marsden/ICR NIHR Biomedical Research Centre. The authors would also like to acknowledge  Dr Katherine A. Hoadley  for normalization and sharing of all of TCGA BRCA RNAseq gene expression data. The work conducted for this project is supported by  BCAC: BCAC  is funded by  Cancer Research UK  [ C1287/A10118 ,  C1287/A12014 ] and by the  European Community ‹s Seventh Framework Programme  under grant agreement number  223175  (grant number  HEALTH-F2-2009-223175 ); COGS: Funding for the iCOGS infrastructure came from: the  European Community 's  Seventh Framework Programme  under grant agreement n›  223175  ( HEALTH-F2-2009-223175 ) (COGS),  Cancer Research UK  ( C1287/A10118 ,  C1287/A 10710 ,  C12292/A11174 ,  C1281/A12014 ,  C5047/A8384 ,  C5047/A15007 ,  C5047/A10692 ,  C8197/A16565 ), the  National Institutes of Health  ( CA128978 ) and  Post-Cancer GWAS initiative  ( 1U19 CA148537 ,  1U19 CA148065  and  1U19 CA148112  -the  GAME-ON initiative ), the  Department of Defence  ( W81XWH-10-1-0341 ), the  Canadian Institutes of Health Research (CIHR)  for the  CIHR Team in Familial Risks of Breast Cancer, Komen Foundation  for the Cure, the  Breast Cancer Research Foundation , and the  Ovarian Cancer Research Fund ; ABCFS: The  Australian Breast Cancer Family Study (ABCFS)  was supported by grant  UM1 CA164920  from the  National Cancer Institute (USA).
021. 007 ); and the  Dutch National Genomics Initiative ; ACP: The ACP study is funded by the  Breast Cancer Research Trust , UK; BBCC: The work of the BBCC was partly funded by  ELAN-Fond of the University Hospital of Erlangen ; BBCS: The BBCS is funded by  Cancer Research UK  and  Breast Cancer Now and acknowledges NHS  funding to the  NIHR Biomedical Research Centre , and the  National Cancer Research Network (NCRN) ;  BIGGS: ES  is supported by  NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust  in partnership with King's  College London, United Kingdom. IT is supported by the  Oxford Biomedical Research Centre ; BSUCH: The BSUCH study was supported by the  Dietmar-Hopp Foundation , the  Helmholtz Society  and the  German Cancer Research Center  (DKFZ); CECILE: The CECILE study was funded by  Fondation de France ,  Institut National du Cancer (INCa) ,  Ligue Nationale contre le Cancer, Ligue contre le Cancer Grand Ouest, Agence Nationale de Sécurité Sanitaire (ANSES) ,  Agence Nationale de la Recherche  ( ANR ); CGPS: The CGPS was supported by the  Chief Physician Johan Boserup and Lise Boserup Fund , the  Danish Medical Research Council and Herlev Hospital ; CNIO-BCS: he  CNIO-BCS  was supported by the  Instituto de Salud Carlos III , the  Red Temática de Investigación Cooperativa en Cáncer  and grants from the  Asociación Española Contra el Cáncer  and the  Fondo de Investigación Sanitario  ( PI11/00923  and  PI12/00070 ); CTS: The CTS was initially supported by the  California Breast Cancer Act of 1993  and the  California Breast Cancer Research Fund  (contract  97-10500 ) and is currently funded through the  National Institutes of Health  ( R01 CA77398 ).
Collection of cancer incidence data was supported by the  California Department of Public Health  as part of the statewide cancer reporting program mandated by  California Health and Safety Code Section 103885. HAC receives support from the  Lon V Smith Foundation  ( LVS39420 ); ESTHER: The ESTHER study was supported by a grant from the  Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the  German Cancer Aid  ( Deutsche Krebshilfe ); GC-HBOC: The  GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer)  is supported by the  German Cancer Aid  (grant no  110837 , coordinator:  Rita K. Schmutzler ); GENICA: The GENICA was funded by the  Federal Ministry of Education and Research (BMBF)   Germany grants   01KW9975/5 ,  01KW9976/8 ,  01KW9977/0  and  01KW0114 , the  Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ) ,  Heidelberg , the  Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA) ,  Bochum , as well as the  Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH ,  Johanniter Krankenhaus , Bonn, Germany; HEBCS: The HEBCS was financially supported by the  Helsinki University Central Hospital Research Fund ,  Academy of Finland  ( 266528 ), the  Finnish Cancer Society, The Nordic Cancer Union  and the  Sigrid Juselius Foundation ; HERPACC: The HERPACC was supported by  MEXT Kakenhi  (No.
Markham ,  Little Rock ,  AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from  National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the  Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR)  of the  Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry; SEARCH: SEARCH is funded by a programme grant from  Cancer Research UK  [ C490/A10124 ] and supported by the  UK National Institute for Health Research Biomedical Research Centre  at the  University of Cambridge ; SEBCS: SEBCS was supported by the  BRL (Basic Research Laboratory ) program through the  National Research Foundation of Korea  funded by the  Ministry of Education, Science and Technology  ( 2012-0000347 ); SGBCC: SGBCC is funded by the  NUS start-up Grant, National University Cancer Institute Singapore (NCIS)   Centre Grant  and the  NMRC Clinician Scientist Award.