testdata: Test data for the snpStats package

Description Usage Format Source Examples

Description

This dataset comprises several data frames from a fictional (and unrealistically small) study. The dataset started off as real data from a screen of non-synonymous SNPs for association with type 1 diabetes, but the original identifiers have been removed and a random case/control status has been generated.

Usage

1

Format

There are five data objects in the dataset:

Source

The data were obtained from the diabetes and inflammation laboratory (see http://www-gene.cimr.cam.ac.uk)

Examples

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Example output

Loading required package: survival
Loading required package: Matrix
A SnpMatrix with  400 rows and  9445 columns
Row names:  1987 ... 1473 
Col names:  173760 ... 290959 
An XSnpMatrix with 400 rows (214 haploid and 186 diploid), and 155 columns
Row names:  1987 ... 1473 
Col names:  174193 ... 290917 
    rownames      chromosome    
 173760 :   1   Min.   : 1.000  
 173761 :   1   1st Qu.: 4.000  
 173762 :   1   Median : 9.000  
 173767 :   1   Mean   : 9.373  
 173769 :   1   3rd Qu.:14.000  
 173770 :   1   Max.   :22.000  
 (Other):9439                   
    rownames  
 174193 :  1  
 174196 :  1  
 174197 :  1  
 174208 :  1  
 174217 :  1  
 174219 :  1  
 (Other):149  
    rownames         cc          sex                 region   
 1      :  1   control:200   Male  :214   Eastern       :124  
 1002   :  1   case   :200   Female:186   North-West    : 66  
 1007   :  1                              South-West    : 55  
 1018   :  1                              North Midlands: 48  
 1020   :  1                              Midlands      : 40  
 1022   :  1                              E & W Ridings : 21  
 (Other):394                              (Other)       : 46  
     Length Class Mode     
rows 18     table character
cols 63     table character
     Length Class Mode     
sex   2     table numeric  
rows 18     table character
cols 84     table character

snpStats documentation built on Nov. 17, 2017, 9:07 a.m.