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Each row of the spreadsheet (Figure 1) corresponds to a single sample. The first column is the names of the .idat files and the remaining columns are the array probes. The table values are β-values, which correspond to the percentage methylation at each site. A β-value is calculated as the ratio of methylated probe intensity over the overall intensity at each site (the overall intensity is the sum of methylated and unmethylated probe intensities). 

 

Figure 1. Spreadsheet after .idat file import: samples on rows (Sample IDs are based on file names), probes on columns, cell values are functionally normalized beta values (default settings)

Before we can perform any analysis, the study samples need to be organized into their experimental groups.

  • Select Add Sample Attributes from the Import section of the Illumina BeadArray Methylation workflow
  • Select Add a Categorical Attribute from the Add Sample Attributes dialog (Figure 2)

Figure 2. Adding sample attributes. Adding Attributes from an Existing Column can be used to split file names into sections, based on delimiters (e.g. _, -, space etc.). Adding a Numeric or Categorical Attribute enables the user to manually specify sample attributes
  • Select OK

The Create categorical attribute dialog allows us to create groups for a categorical attribute. By default, two groups are created, but additional groups can be added. 

  • Set Attribute name: to Cell Type
  • Rename the groups B cells and LCLs
  • Drag and drop the samples from the Unassigned list to their groups as listed in the table below
Sample IDCell Type
GSM2452106_200483200025_R04C01B cells
GSM2452107_200483200021_R01C01B cells
GSM2452108_200483200021_R02C01B cells
GSM2452109_200483200025_R06C01B cells
GSM2452110_200483200025_R07C01B cells
GSM2452111_200483200021_R08C01B cells
GSM2452112_200483200021_R06C01B cells
GSM2452113_200483200021_R04C01B cells
GSM2452114_200483200025_R01C01LCLs
GSM2452115_200483200025_R03C01LCLs
GSM2452116_200483200021_R03C01LCLs
GSM2452117_200483200025_R05C01LCLs
GSM2452118_200483200025_R02C01LCLs
GSM2452119_200483200021_R07C01LCLs
GSM2452120_200483200021_R05C01LCLs
GSM2452121_200483200025_R08C01LCLs

There should now be two groups with eight samples in each group (Figure 3).

 

Figure 3. Adding Cell Type attribute as a categorical group
  • Select OK
  • Select Yes from the Add another categorical attribute dialog
  • Set Attribute name: to Gender
  • Rename the groups Male and Female
  • Drag and drop the samples from the Unassigned list to their groups as listed in the table below
Sample IDGender
GSM2452106_200483200025_R04C01Female
GSM2452107_200483200021_R01C01Female
GSM2452108_200483200021_R02C01Male
GSM2452109_200483200025_R06C01Female
GSM2452110_200483200025_R07C01Female
GSM2452111_200483200021_R08C01Female
GSM2452112_200483200021_R06C01Female
GSM2452113_200483200021_R04C01Male
GSM2452114_200483200025_R01C01Female
GSM2452115_200483200025_R03C01Female
GSM2452116_200483200021_R03C01Male
GSM2452117_200483200025_R05C01Female
GSM2452118_200483200025_R02C01Female
GSM2452119_200483200021_R07C01Female
GSM2452120_200483200021_R05C01Female
GSM2452121_200483200025_R08C01Male

There should now be two groups with four samples in Male and twelve samples in Female (Figure 4).

Figure 4. Adding Gender attribute as a categorical group
  • Select OK
  • Select No from the Add another categorical attribute dialog
  • Select Yes to save the spreadsheet

Two new columns have been added to spreadsheet 1 (Methylation) with the cell type and gender of each sample (Figure 5). 

 

Figure 5. Annotated beta values spreadsheet
 

 

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