Description Usage Arguments Value Examples
Detect subpopulations using NMF
1 2 3 4 | nmf_subpopulation(expr_matrix_, n_subpop_ = 2, log_transformation_ = T,
verbose_level_ = 1, n_threads_ = 1, nrun_ = 30, method_ = "brunet",
top_genes_facet_title_font_size_ = 24, .options_ = sprintf("p%dv%d",
n_threads_, verbose_level_ - 1), seed_ = 12345)
|
expr_matrix_ |
The expression matrix, each row is a gene and each
column is a sample. The row names should be gene symbols and the column
names should be sample ids. Use the correct capticalization for gene
symbols. For mouse genes,only the first letter is capitalized (e.g. Tp53);
for human genes, all letters are capitalized (e.g. TP53). The values will
be log-transformed by default, this can be changed using the
|
n_subpop_ |
The number of expected subpopulations. Default: 2. |
log_transformation_ |
Whether to log-transform the expression matrix.
A pseudo count |
verbose_level_ |
How much information is printed. 0 = quiet, 1 = normal, 2 = with debug info, 3 = with extra debug info. Default: 1. |
n_threads_, nrun_, method_, .options_, seed_ |
Parameters for |
method_ |
Interative method for NMF. See the documentation of |
seed_ |
Random seed. |
A list with the following elements
nmf_result
The NMFfitX1
object returned by the nmf
call.
gene_info
A data_frame
detailing the bases, weighted bases,
and D-score for each gene. The data frame is sorted by their D-scores
d_score_frequency_plot
Kernal distribution for the D-scores, separated by the coef components they represent.
ordered_sample_ids
The pseudo-order of samples calculated by sorting the differences of coef values for each sample.
coef_line_dat
Plotting data for coef_line_plot
coef_line_plot
A line plot showing the trend formed by the coef values, using the order in ordered_sample_ids
.
path_dat
Plotting data for pca_path_plot
and mds_path_plot
.
pca_path_plot
Connecting the PCA plot of the expression matrix using the order in ordered_sample_ids
.
The thickness of the lines indicate the jump of differences of the coef values.
mds_path_plot
Same as pca_path_plot
, except for MDS plot. The distance is "1 - Pearson Correlation".
top_genes_dat
Plotting data for top_genes_free_y_plot
and top_genes_fixed
.
top_genes_free_y_plot
Faceted bar-plot showing the expression levels of the top 100 genes, across all samples.
Samples are sorted using the order in ordered_sample_ids
.
top_genes_fixed
Sample as top_genes_free_y_plot
, except all y-axes are fixed across all faceted.
1 | res <- nmf_subpopulation(toy)
|
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