By Margi Sheth, Julia Zhang, Jean C Zenklusen
Collaborative Genomics tasks: A complete Guide comprises operational strategies, coverage concerns, and the numerous classes realized by way of The melanoma Genome Atlas venture. This publication courses the reader via equipment in sufferer pattern acquisition, the institution of knowledge new release and research pipelines, info garage and dissemination, qc, auditing, and reporting.
This publication is vital for these seeking to organize or collaborate inside of a large-scale genomics examine venture. All authors are individuals to The melanoma Genome Atlas (TCGA) software, a NIH- funded attempt to generate a complete catalog of genomic changes in additional than 35 melanoma types.
As the price of genomic sequencing is lowering, a growing number of researchers are leveraging genomic information to notify the biology of affliction. the quantity of genomic information generated is becoming exponentially, and protocols have to be confirmed for the long term garage, dissemination, and legislation of this information for learn. The book's authors create an entire guide at the administration of study initiatives concerning genomic info as realized throughout the evolution of the TCGA software, a undertaking that used to be essentially conducted within the US, yet whose influence and classes realized should be utilized to overseas audiences.
- Establishes a framework for handling large-scale genomic learn tasks related to a number of collaborators
- Describes classes realized via TCGA to arrange for power roadblocks
- Evaluates coverage concerns which are had to steer clear of pitfalls
- Recommends ideas to make undertaking administration extra efficient
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Extra info for Collaborative genomics projects : a comprehensive guide
51 52 CHAPTER 6 Pipeline: Data Storage and Dissemination ■ Redistribute data and metadata tailored to diverse project stakeholders and end users Depending on the scale of the project, the DCC should have the capability to handle several terabytes of genomic data. For example, the two main databases that store TCGA data: the Data Coordination Center (DCC) and Cancer Genomics Hub (CGHub) ingest 100 TB of data and distribute about 800 TB of data each month to over 8000 unique end users. It is very important that the DCC can meet the technical requirements of project.
An exploratory study that does not depend upon outcome data or an expected end result also needs initial questions based upon established knowledge to guide the analysis process. TCGA tumor analysis projects had some questions common to all tumor types, and some individual questions unique to each tumor type. These questions were usually first developed when the clinical data collection forms were created. Questions related to tumor scoring and known risk factors (eg, asbestos exposure and mesothelioma ) were included on the forms so that the data would be available for answering these initial questions.
9] Laxman B, Morris DS, Yu J, Siddiqui J, Cao J, Mehra R, et al. A first-generation multiplex biomarker analysis of urine for the early detection of prostate cancer. Cancer Res 2008;68(3):645À9. pdf. [cited October 5, 2015]. Chapter 6 Pipeline: Data Storage and Dissemination INTRODUCTION When a large-scale genomics research project involves many data generation centers and different types of high-volume data, a central data management system needs to be developed. The central data management center serves as the main hub for data upload and download.