Dear developers,
I encountered an issue when using the cluster() function from the RichCluster package. The error occurs in the line:
merged_df <- merged_df %>% filter(Pvalue < min_value)
Problem description:
-
Missing 'Pvalue' column error:
Despite my input dataframe containing a "Pvalue" column, the code throws an error: "object 'Pvalue' not found".
-
Preference for Padj instead of Pvalue:
I intend to filter by the Padj column (corrected p-values) rather than raw Pvalue. However, the current implementation hardcodes Pvalue, limiting flexibility. A parameter to specify the p-value column (e.g., p_column = "Padj") would greatly enhance usability.
-
Missing dplyr dependency handling:
While RichCluster depends on dplyr, it does not internally load the package with library(dplyr), causing pipeline failures unless users manually load it beforehand. Explicitly importing dplyr functions or adding library(dplyr) to internal code would resolve this.
Best regards
Dear developers,
I encountered an issue when using the cluster() function from the RichCluster package. The error occurs in the line:
merged_df <- merged_df %>% filter(Pvalue < min_value)Problem description:
Missing 'Pvalue' column error:
Despite my input dataframe containing a "Pvalue" column, the code throws an error: "object 'Pvalue' not found".
Preference for Padj instead of Pvalue:
I intend to filter by the Padj column (corrected p-values) rather than raw Pvalue. However, the current implementation hardcodes Pvalue, limiting flexibility. A parameter to specify the p-value column (e.g., p_column = "Padj") would greatly enhance usability.
Missing dplyr dependency handling:
While RichCluster depends on dplyr, it does not internally load the package with library(dplyr), causing pipeline failures unless users manually load it beforehand. Explicitly importing dplyr functions or adding library(dplyr) to internal code would resolve this.
Best regards