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To detect differential methylation between CpG loci in different HSCP populations, go to Analysis > Detect Differential Methylation. In the ANOVA dialog (Figure 1), select Add Factor to move the factor 2. HPSC from Experimental Factor(s) to the ANOVA Factor(s) box.

Genomics Suite Documentation > Detect differentially methylated loci > ANOVA_Setup.png

Depending on the data in the top level (i.e. parent) spreadsheet you may need to manually specify whether the data is already log transformed: you should select Yes for M-values, as they are based on logit transformation (Figure 2). By default, Partek Genomics Suite will calculate fold-change value for each contrast and, in addition to that, if you want to include the difference in methylation levels between the groups at each CpG site in the output, check the Estimate box in the Other Statistics section of the dialog (Figure 2). The setup of the contrasts has implications on downstream steps, in particular on filtering the differentially methylated loci.

Genomics Suite Documentation > Detect differentially methylated loci > Setting_ANOVA_Contrasts.png

For this exercise, we shall compare primed HPSC with suppression of OCT4 (shPOU5F1) and primed HPSC with suppression of NANOG (shNANOG) with the baseline primed cells. To start with, select the Primed group in the Candidate Level(s) box and push Add Contrast Level > to move the Primed group to Group 2 (lower box). Then Ctrl & select both shPOU5F1 and shNANOG in the Candidate Level(s) box and push Add Contrast Level > to move them to Group 1 (upper box). Then click Add Combinations and confirm that two contrast have been created as seen in Figure 3.

Genomics Suite Documentation > Detect differentially methylated loci > two_contrasts_specified.png

Push OK to confirm the contrast (and close the contrast dialog) and again to start the ANOVA calculation.

The first time you use MethylationEPIC array, the manifest file needs to be configured and the window like the one in Figure 4 will pop up. First select the second option (Chromosome is in one column and the physical location is in another column). Marker ID is on the first column (Ilmn ID), Chromosome is on the column CHR, while the Physical Position is on the MAPINFO column. Set according to Figure 4 and select Close. This enable Partek Genomics Suite to parse out probe annotation from the manifest file.

Genomics Suite Documentation > Detect differentially methylated loci > Configure_Annotation.png

The result of 1-way ANOVA is shown in Figure 5. Each row of the table represents a single CpG locus (identified by Probeset ID column). The remaining columns contain the following information:

Column 3. Gene Symbol: the gene overlapping the probe as specified in the Illumina manifest file

Column 4. p-value(HPSC): overall p-value for the specified factor (in parenthesis). A low p-value indicates that there is a difference in methylation between the levels of this attribute (i.e. study groups). The contrast p-values should then be used to evaluate individual group comparisons. If more than one factor is included in the model, p-value will be reported for each.

Next, for each contrast included in the model, a block of seven columns will be added, as follows:

Column 5. p-value(shNANOG vs. Primed): p-value for the given contrast (in parenthesis). A low p-value indicates a difference in methylation between the groups included in the contrast (here: shNANOG and Primed).

Column 6. Ratio(shNANOG vs. Primed): ratio of average methylation level in one over the other the other contrasted group (shNANOG and Primed, respectively). Ratio is reported in linear space.

Column 7. Fold Change(shNANOG vs. Primed): fold-change in one over the other contrasted group (shNANOG and Primed, respectively). Fold-change is reported in linear space.

Column 8. Fold Change(shNANOG vs. Primed) (Description): if fold-change > 1, it means hypermethylation in the first group (e.g. shNANOG up vs Primed), if fold-change < -1, it means hypomethylation in the first group (e.g. shNANOG down vs Primed), relative to the second group (Primed). This column enables quick filtering

Columns 9. & 10. Lower and upper (respectively) limits of 95% confidence interval of the fold-change

Column 11. Estimate(shNANOG vs. Primed): difference between means of two groups (i.e. shNANOG and Primed) (this column is optional and depends on the way contrasts were set up)

Columns 12. - 18. correspond to columns 5. - 11.

Columns 19.+ Statistical output

Genomics Suite Documentation > Detect differentially methylated loci > ANOVA_spreadsheet.png

Going forward, analysis of differentially methylated loci typically includes removal of the probes on X and Y chromosomes (to avoid the problems with inactivation of one X chromosome). To annotate the ANOVA spreadsheet with the information required for filtering, right-click on the Gene Symbol column, select Insert Annotation, tick-mark the CHR filed (Figure 6) and push OK. A new column will be appended to the spreadsheet.

Genomics Suite Documentation > Detect differentially methylated loci > Adding_Annotation.png

To enable filtering right-click on the header of the CHR column > Properties and set the type to categorical (and OK). Now, activate the Interactive Filter tool () . If needed use the drop-down list to point to the CHR column. The column chart represents the number of appearances of each chromosome in the spreadsheet (i.e. the number of probes per chromosome). To remove the probes on the X and the Y chromosome left click on the two right-most columns (the pop up balloon will show you the chromosome label) and the columns will be grayed out (Figure 7).

Genomics Suite Documentation > Detect differentially methylated loci > Interactive_Filter.png

After removal of the probes on the sex chromosomes, let us extract all the autosomal probes to a new spreadsheet. Right click on the ANOVA 1-way spreadsheet > Clone... Set the Name of new spreadsheet to AutosomalOnly and make it a child of the top-level spreadsheet (EPIC iDAT) (Figure 8). Push OK. The newly created autosomalonly spreadsheet will be a new starting point for all the downstream steps.

Genomics Suite Documentation > Detect differentially methylated loci > Clone_Spreadsheet.png

To come up with a list of differentially methylated loci, proceed to the workflow and select Create Marker List. That will open the List Manager functionality and you will be on the ANOVA Streamlined tab. Factors in the model are listed in the top section, contrasts specified in the model are in the middle, while the filter settings are at the bottom.

Select shNANOG vs Primed contrast to see the current filter configuration. By default, both fold-change and p-value with false discovery rate correction are applied, with the number of CpG loci passing the filter given as # Pass.

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