| Title: | Calculate Correlations and Estimate Causality | 
| Version: | 0.1.3 | 
| Description: | This tool performs pairwise correlation analysis and estimate causality. Particularly, it is useful for detecting the metabolites that would be altered by the gut bacteria. | 
| URL: | https://github.com/sugym/CausCor | 
| License: | MIT + file LICENSE | 
| Language: | en-US | 
| Encoding: | UTF-8 | 
| RoxygenNote: | 7.1.2 | 
| Imports: | cowplot, dplyr, ggplot2, grDevices, magrittr, stats, WriteXLS | 
| Suggests: | testthat (≥ 3.0.0) | 
| Config/testthat/edition: | 3 | 
| NeedsCompilation: | no | 
| Packaged: | 2023-11-10 05:33:40 UTC; sugiyamatomomi | 
| Author: | Tomomi Sugiyama [aut, cre] | 
| Maintainer: | Tomomi Sugiyama <sugiyama.t.am@m.titech.ac.jp> | 
| Repository: | CRAN | 
| Date/Publication: | 2023-11-10 05:50:02 UTC | 
Make list of A-B pair causal correlations - 40% Filtering version
Description
Make list of A-B pair causal correlations - 40% Filtering version
Usage
filter_40(
  a_mat,
  b_mat,
  a_category,
  b_category,
  min_cor,
  min_r2,
  min_sample = ceiling((ncol(a_mat) - 1) * 0.4),
  max_sample = ncol(a_mat) - 1 - min_sample
)
Arguments
a_mat | 
 Matrix of measurements of A for each sample.  | 
b_mat | 
 Matrix of measurements of B for each sample.  | 
a_category | 
 Category name of A.  | 
b_category | 
 Category name of B.  | 
min_cor | 
 Minimum spearman correlation coefficient.  | 
min_r2 | 
 Minimum R2 score.  | 
min_sample | 
 Minimum number of samples. The default is 40% of the total samples.  | 
max_sample | 
 Maximum number of samples. The default is 60% of the total samples.  | 
Make list of A-B pair causal correlations
Description
Make list of A-B pair causal correlations
Usage
filter_cc(
  a_mat,
  b_mat,
  a_category,
  b_category,
  min_cor,
  min_r2,
  min_sample,
  max_sample = ncol(a_mat) - 1,
  direction = T
)
Arguments
a_mat | 
 Matrix of measurements of A for each sample.  | 
b_mat | 
 Matrix of measurements of B for each sample.  | 
a_category | 
 Category name of A.  | 
b_category | 
 Category name of B.  | 
min_cor | 
 Minimum spearman correlation coefficient.  | 
min_r2 | 
 Minimum R2 score.  | 
min_sample | 
 Minimum number of samples.  | 
max_sample | 
 Maximum number of samples. The default is the total number of samples.  | 
direction | 
 Extract only directional associations where a change in category A causes a change in category B. The default is True.  | 
Make list of A-B pair causal correlations - Normal Filtering version
Description
Make list of A-B pair causal correlations - Normal Filtering version
Usage
filter_n(a_mat, b_mat, a_category, b_category, min_cor, min_r2, min_sample)
Arguments
a_mat | 
 Matrix of measurements of A for each sample.  | 
b_mat | 
 Matrix of measurements of B for each sample.  | 
a_category | 
 Category name of A.  | 
b_category | 
 Category name of B.  | 
min_cor | 
 Minimum spearman correlation coefficient.  | 
min_r2 | 
 Minimum R2 score.  | 
min_sample | 
 Minimum number of samples.  | 
Save scatter plots
Description
Save scatter plots
Usage
plot_16(a_mat, b_mat, list, out_info, x_italic = F, y_italic = T)
Arguments
a_mat | 
 Matrix of measurements of A for each sample.  | 
b_mat | 
 Matrix of measurements of B for each sample.  | 
list | 
 List of results.  | 
out_info | 
 Output directory.  | 
x_italic | 
 Italicize the x-axis label of the plot. The default is False.  | 
y_italic | 
 Italicize the y-axis label of the plot. The default is True.  | 
Save list as a text file
Description
Save list as a text file
Usage
save_text(list, out_info, file_type)
Arguments
list | 
 List of results.  | 
out_info | 
 Output directory.  | 
file_type | 
 Choose from "excel", "csv", "tsv".  |