Description Usage Value Source
Hill, LaPan, Li and Haney (2007) develop models to predict which cells in a high content screen were well segmented.
The data consists of 119 imaging measurements on 2019. The original analysis used 1009 for training and 1010 as a test set (see the column called Case
).
The outcome class is contained in a factor variable called Class
with levels "PS" for poorly segmented and "WS" for well segmented.
The raw data used in the paper can be found at the Biomedcentral website. Versions of caret < 4.98 contained the original data. The version now contained in segmentationData
is modified. First, several discrete versions of some of the predictors (with the suffix "Status") were removed. Second, there are several skewed predictors with minimum values of zero (that would benefit from some transformation, such as the log). A constant value of 1 was added to these fields: AvgIntenCh2
, FiberAlign2Ch3
, FiberAlign2Ch4
, SpotFiberCountCh4
and TotalIntenCh2
.
A binary version of the original data is at http://caret.r-forge.r-project.org/segmentationOriginal.RData.
1 |
segmentationData |
data frame of cells |
Hill, LaPan, Li and Haney (2007). Impact of image segmentation on high-content screening data quality for SK-BR-3 cells, BMC Bioinformatics, Vol. 8, pg. 340, http://www.biomedcentral.com/1471-2105/8/340.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.