The aim of PRECISIONDATA
, a data package, is to compliment the PRECISION
package (can be found here). PRECISIONDATA
contains a number of datasets (before and after pre-processed) that can be used as arguments for the functions in the PRECISION
package.
The two core datasets are noba.uhdata.log2
and noba.nuhdata.log2
, both probe-level data. The unique pair of datasets are generated from the same set of 96 endometrial and 96 ovarian tumor samples using different experimental handling designs. The first dataset was handled by one technician in one run and its arrays were randomly assigned to tumor samples using blocking (by both array slide and row-column location on each slide). The second dataset was handled by two technicians in multiple batches. Its arrays were assigned in the order of sample collection without blocking to mimick typical practice. More detailed descriptions can be found in Qin et al. The former dataset is referred to as the 'uniformly-handled' dataset and the latter dataset as the 'nonuniformly-handled' dataset.
Each of the two datasets has two auxiliary datasets: one probe-truncated dataset and one probe-summarized dataset. For example, noba.uhdata.log2
is the uniformly-handled probe-level dataset and noba.uhdata.log2.p10
is the probe-truncated dataset that has 10 probes per unique probe set, and noba.uhdata.log2.p10.psl
is the probe-summarized dataset (i.e., on the probe-set-level).
PRECISIONDATA
package is currently availabe on GitHub. To load the package, type the following command in R console:
library(devtools) # devtools is required install_github("rebeccahch/precisiondata") library(PRECISIONDATA)
To fetch data, use the following code:
data("noba.uhdata.log2") data("noba.nuhdata.log2")
When PRECISIONDATA
is used, please cite the following papers:
Huang HC, Qin LX. PRECISIONDATA: an R data package containing a unique pair of Agilent microarray datasets differed by study designs (2016). GitHub repository, https://github.com/rebeccahch/precisiondata.
Qin LX, Huang HC, Begg CB. Cautionary Note on Cross Validation in Molecular Classification. Journal of Clinical Oncology. 2016. [in press].
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.