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More and more large data collections are gathered worldwide in various IT systems.
As more large data sets become available, it will be useful to extend these studies to better define the magnitude of gene expression variation in purebred animals and in outbred humans across a variety of tissues.
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"People are more and more interested in large data sets that have a scale as large as a continent, and no one person is going to collect that," she said.
Dr. Sarah Creighton, gynecologist and the study's lead investigator, is quoted as saying "there is little information about what is normal," with her team encouraging the publication of more large-scale data on normal labial measurements.
Moreover, Iwata and Jannink (2011) simulated the accuracy of GS using more large-scale data, consisting of 1325 SNPs in 863 breeding lines of barley derived from nine breeding programmes in the USA.
However, a large volume of genome-wide molecular neuropharmacology data, such as microarray gene expression [ 31] and genome-wide association studies [ 32], is available, and more large-scale data will be available in the near future due to the rapid advances in genome-wide technologies and strong support from pharmacology communities.
Moreover, the performance gain of the CSPA is even more significant for large data files.
This is more evident on large data repositories such as YouTube and cloud storage.
One was Dirk Neumann from "social supercomputer" startup Opani, which provides tools to help people more easily analyze large data sets.
However, more, large scaled MRI data sets are becoming available allowing for independent replication testing.
They are more suitable for large data sets to reduce the effect of sampling variation and ensure reasonable extrapolation.
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