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Sage / DREAM Breast Cancer Prognosis Challenge

Sage / DREAM Breast Cancer Prognosis Challenge.

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Sage / DREAM Breast Cancer Prognosis Challenge

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  1. Sage / DREAM Breast Cancer Prognosis Challenge The goal of the breast cancer prognosis challenge is to assess the accuracy of computational models designed to predict breast cancer survival based on clinical information about the patient's tumor as well as genome-wide molecular profiling data including gene expression and copy number profiles. More… (next page)

  2. Sage / DREAM Breast Cancer Prognosis Challenge Clinical Problem Molecular diagnostics for cancer therapeutic decision making are among the most promising applications of genomic technology. Several diagnostic tests have gained regulatory approval in recent years. Molecular profiles have proved particularly powerful in adding molecular information to standard clinical practice in breast cancer, using gene-expression-based diagnostic tests such as Mammaprint and OncotypeDx. The exciting phase of “Precision Medicine”, as defined by the Institute of Medicine Report last year, proposes a world where medical decisions will be guided by molecular markers that ensure that therapies are tailored to the patients that receive them. The most exciting topics at the FDA and in the scientific community revolve around – “how can we leverage genomic information to determine who should and should not get which therapies?” Data Formats • Survival data • Survival data is loaded into R as a Surv object as defined in the R survivalpackage. This object is simply a 2 column matrix with sample names on the rows and columns: • time – time from diagnosis to last follow up. • status – weather the patient was alive at last follow up time. • Feature data • Gene expression data. • Performed on the Illumina HT 12v3 platform and normalized using XXXX. • Loaded as BioconductorExpressionSet object with columns corresponding to samples and rows corresponding to Illumina probes. • Copy number data. • Performed on the Affymetrix SNP 6.0 platform and normalized using XXX. • Loaded as BioconductorExpressionSet object with columns corresponding to samples and rows corresponding to segmented copy number regions (??). • Clinical covariates. For a detailed explanation of the clinical data and how it is currently used in breast cancer prognosis and treatment, see Breast Cancer Challenge clinical background. R-Studio Tutorial Discussion Forum Google Technical Guide Join the Challenge Contest Computing Facilities Powered by Google (next page)

  3. Join the Sage/DREAM Challenge • First, register for a Synapse account and sign-in. • Second, sign the Non-disclosure agreement and submit your application. • You will be notified by email when your application is approved. • In the meantime, you may review the technical documentation on discussion forum. Contest Computing Facilities Powered by Google (Synapse log in page) (next page) (previous page)

  4. Non-Disclosure Agreement By clicking “I Agree” you are agreeing to the following NDA and applying to the Sage/DREAM challenge. Loremipsum dolor sit amet, consectetueradipiscingelit. Nam nibh. Nuncvariusfacilisiseros. Sederat. In in velitquisarcuornarelaoreet. Curabituradipiscingluctusmassa. Integer utpurus ac auguecommodocommodo. Nuncnec mi eujustotemporconsectetuer. Etiam vitae nisl. In dignissim lacus ut ante. Craselitlectus, bibendum a, adipiscing vitae, commodo et, dui. Uttincidunttortor. Donecnonummy, enim in laciniapulvinar, velittellusscelerisqueaugue, ac posuereliberournaegetneque. Crasipsum. Vestibulumpretium, lectusnecvenenatisvolutpat, puruslectusultricesrisus, a condimentumrisus mi et quam. Pellentesqueauctorfringillaneque. Duiseumassautloremiaculisvestibulum. Maecenas facilisiselitsedjusto. Quisquevolutpatmalesuadavelit. Nunc at velitquislectusnonummyeleifend. Curabitureros. Aenean ligula dolor, gravidaauctor, auctor et, suscipit in, erat. Sedmalesuada, enimutconguepharetra, massaelitconvallispede, ornarescelerisqueliberonequeutneque. In at libero. Curabiturmolestie. Sedvelneque. Proin et dolor ac ipsumelementummalesuada. Praesent id orci. Donechendrerit. In hachabitasseplateadictumst. Aenean sit ametarcu a turpisposuerepretium. Nullamaurisodio, vehicula in, condimentum sit amet, tempus id, metus. Donec at nisi sit ametfelisblanditposuere. Aliquameratvolutpat. Craslobortisorci in quam porttitorcursus. Aeneandignissim. Curabiturfacilisissem at nisi laoreetplacerat. Duissedipsum ac nibhmattisfeugiat. Proinsedpurus. Vivamuslectusipsum, rhoncussed, scelerisque sit amet, ultrices in, dolor. Aliquamvel magna non nuncornarebibendum. Sedlibero. Maecenas at est. Vivamusornare, felis et luctusdapibus, lacus leoconvallisdiam, egetdapibusauguearcuegetarcu. Fusceauctor, metuseuultriciesvulputate, sapiennibhfaucibus ligula, egetsollicitudinauguerisus et dolor. Aeneanpellentesque, tortor in cursusmattis, ante diammalesuada ligula, ac vestibulumnequeturpisutenim. Crasornare. Proin ac nisi. Praesentlaoreet ante temporurna. In imperdiet. Nam utmetus et orcifermentumnonummy. Crasvelnunc. Donecfeugiatnequeegetpurus. Quisquerhoncus. Phasellus tempus massaaliqueturna. Integer fringilla quam eget dolor. Curabiturmattis. Aliquam ac lacus. In congue, odiouttristiqueadipiscing, diamleofermentumipsum, necsollicitudin dui quam et tortor. Proin id neque ac pedeegestaslacinia. Curabitur non odio. I Agree Cancel

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