22. beta_tSNE
22.1. Overview
beta_tSNE performs t-distributed stochastic neighbor embedding (t-SNE) on
DNA methylation samples.
The input matrix must have CpGs in rows and samples in columns. CpGs are treated as features and samples as observations.
A sample-group file is optional and can be used to color samples in the plot.
22.2. Input Files
22.2.1. Beta matrix
The first column contains CpG IDs and the remaining columns contain sample Beta-values. Common delimiters and compressed input are supported.
Example:
CpG_ID Sample_01 Sample_02 Sample_03 Sample_04
cg_001 0.831035 0.878022 0.794427 0.880911
cg_002 0.249544 0.209949 0.234294 0.236680
cg_003 0.845065 0.843957 0.840184 0.824286
CpG IDs and sample IDs must be unique.
22.2.2. Group file
The optional group file contains two columns: sample ID and group label. Comma- and tab-delimited files are supported, with or without a header.
Example:
Sample,Group
Sample_01,normal
Sample_02,normal
Sample_03,tumor
Sample_04,tumor
If a group file is supplied, every sample in the Beta matrix must be present in the group file.
If no group file is supplied, all samples are assigned to one group named
All_samples.
22.3. Missing Values and Preprocessing
By default:
CpGs containing any missing value are removed.
zero-variance CpGs are removed.
CpG features are standardized across samples before t-SNE.
Use --na_policy impute to replace missing values with the per-CpG mean.
CpGs containing only missing values are removed before imputation.
Use --no_standardize to skip feature standardization.
22.4. Usage
Basic usage:
beta_tSNE \
-i cirrHCV_vs_normal.data.tsv \
-g cirrHCV_vs_normal.grp.csv \
-o HCV_vs_normal
Useful options include:
-p,--perplexity– t-SNE perplexity (default: 5.0); must be smaller than the number of samples-n,--n_components,--ncomponent– embedding dimensions, either 2 or 3 (default: 2)--max_iter,--n_iter– maximum optimization iterations (default: 5000)--learning_rate–autoor a positive numeric value (default:auto)--init {pca,random}– initialization method (default:pca)--metric– distance metric accepted by scikit-learn t-SNE (default:euclidean)--early_exaggeration– early-exaggeration factor (default: 12.0)--seed– random seed (default: 0)--na_policy {drop,impute}– missing-value handling (default:drop)--no_standardize– skip CpG standardization--label– add sample IDs to the plot--marker {circle,dot}– plot marker style (default:circle)--alpha– point opacity (default: 0.8)--point_size– point size (default: 45)--legend_location– legend position (default:best)--format {png,pdf,both}– plot format (default:pdf)--dpi– PNG resolution (default: 300)--width/--height– plot size in inches (default: 8 x 8)--no_plot– write coordinates without generating a plot-o,--out_prefix,--output– output prefix
Display all options with:
beta_tSNE -h
22.5. Output
For output prefix HCV_vs_normal, the command always writes:
HCV_vs_normal.tSNE.tsv– t-SNE coordinates and group labels
Unless --no_plot is used, it also writes one or more plots:
HCV_vs_normal.tSNE.pdfHCV_vs_normal.tSNE.png
Use --format both to generate both plot formats.
The coordinate table contains tSNE1 and tSNE2 for a 2D embedding,
and also tSNE3 when --n_components 3 is used. Plotting always uses the
first two dimensions.
22.6. Example Data
22.7. Example Figure
