30. dmc_nonparametric

30.1. Overview

dmc_nonparametric performs differential CpG analysis using nonparametric tests on DNA methylation Beta-values.

The test is selected automatically from the number of biological groups:

Number of groups	Test
2	Two-sided Mann-Whitney U test
3 or more	Kruskal-Wallis H-test

The input matrix must have CpGs/probes in rows and samples in columns.

30.2. Input Files

30.2.1. Beta-value matrix

The first row contains sample IDs and the first column contains CpG/probe IDs.

Example:

CpG_ID      Sample_01   Sample_02   Sample_03   Sample_04
cg00001099  0.775       0.812       0.623       0.598
cg00000363  0.611       0.602       0.470       0.455

Sample IDs must be unique.

Non-numeric and non-finite values are treated as missing and ignored. Plain text, .gz, .bz2, and other formats supported by the CpGtools reader may be used.

30.2.2. Group file

The group file is a comma-separated, two-column file with a header:

column 1: sample ID
column 2: group ID

At least two groups are required.

Example:

Sample,Group
Sample_01,Control
Sample_02,Control
Sample_03,Case
Sample_04,Case

Sample IDs in the group file must be unique and must occur in the methylation matrix.

Samples present in the methylation matrix but absent from the group file are ignored.

30.3. Method

30.3.1. Two groups

For exactly two groups, dmc_nonparametric performs a two-sided Mann-Whitney U test using scipy.stats.mannwhitneyu.

If either group has no valid observations for a CpG, the test result is missing.

30.3.2. Three or more groups

For three or more groups, the command performs a Kruskal-Wallis H-test using scipy.stats.kruskal.

Groups with no valid observations for a particular CpG are omitted from that CpG’s test. If fewer than two groups contain valid observations, the result is missing.

After testing all CpGs, valid p-values are adjusted using the CpGtools Benjamini-Hochberg multiple-testing procedure.

30.4. Usage

Two-group analysis:

dmc_nonparametric \
    -i test_05_TwoGroup.tsv.gz \
    -g test_05_TwoGroup.grp.csv \
    -o U_test

Three-group analysis:

dmc_nonparametric \
    -i test_06_ThreeGroup.tsv.gz \
    -g test_06_ThreeGroup.grp.csv \
    -o H_test

Available options are:

-i, --input_file – Beta-value matrix
-g, --group – sample/group file
-o, --output – output prefix
--version – show the CpGtools version

Display all options with:

dmc_nonparametric -h

30.5. Output

For output prefix U_test, the command writes:

U_test.pval.txt

The original input table is preserved and two columns are appended:

Column	Description
`pval`	Raw Mann-Whitney U or Kruskal-Wallis p-value.
`adj.pval`	Benjamini-Hochberg FDR-adjusted p-value.

Missing statistical results are written as NaN and are excluded from multiple-testing correction.

30.6. Input-row Handling

If a CpG row contains fewer data fields than the header, missing values are padded with NaN. Extra fields are ignored. A warning is written in either case.

The original input line is preserved in the final output; only pval and adj.pval are appended.

30.7. Example Data

Two groups:

Three groups: