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As Charlie mentioned hopefully my computer exacting a little strength this morning this will work okay we're going to talk about the Cancer Genome Atlas the publicly available data and how you could use this in your research so a little of background about the CGA project this is a large-scale collaborative efforts that was spearheaded by the NIH a few years back with a pilot project looking at nuroblastoma samples the idea is to create a comprehensive map of the genomic changes and different types of cancers after the initial pilot project the goal was expanded with the additional funding from the Recovery Act and the current goal is to examine over 11,000 samples across 20 different cancer types one of the major objectives or the goals of the CGA project has been to disseminate the data information as fast as it gets generated through a public access data based repository and that's they have done an excellent job at that and the data is available at different levels we'll talk about that and if it is ultimate goal of course is to improve cancer diagnosis treatment and prevention all this data is actually comes from their website so if you go to the CGA website as of a couple of days ago you can find a list of the different cancer types like the AML and bladder etc and how many samples that they have collected and how many of them are ready for being downloaded and at different levels most what I mean download this is just taking big files down and so you can see there's quite a bit of cancers and quite a bit of samples available now what are the different types of data that is being collected, so first there are for each sample typically in all the cases that I've seen it includes the tumor genomic profile of the tumor the maps around the normal tissue and the blood drive normal for the same individual and samples were processed at multiple sites using different platforms this was actually true for the pilot project with GBM and nuroblastoma where the ACTH Angeles algo raids were used at a couple side kicking cardboard and foam catering and then snip arrays from Illumine and half metrics were used to profile the same samples at other institutions and to look at if there are any biases or differences between different platforms, so there's comprehensive data there in addition to the genomic profile there is also a lot of phenotypic well some phenotypic data for example, and it depends the extent of that really depends on the different types of samples but most often all the ones I've seen include survival data which is also very nice to have for doing the biomarker discovery type of research now along another dimension there is the genomic data there's an in addition to copy number there's gene expression methylation mutation LOW data that's being measured in RAW format to get that so how do you access this data so what the CGA has defined or NIH NCBI horror is the authority up there as defined for levels of access there is level one which is...
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