Function reference • tgutil

All functions
`call_main()`	Call `main()`
`clip_vals()`	Clips numeric values so that they lie in the range [min_val, max_val] Works on both numeric arrays and dataframes
`colMaxs()`	A wrapper for matrixStats::colMaxs() Returns the minimal numeric value per column in a matrix or a dataframe
`colMins()`	A wrapper for matrixStats::colMins() Returns the minimal numeric value per column in a matrix or a dataframe
`cutree_order()`	Cut a tree into groups of data in the order of the tree
`exit()`	Equivalent to python's sys.exit() Stop the script without saving R's status.
`fread()`	Wrapper for data.table::fread. Returns a data.frame instead of a data.table
`fread_mm()`	Efficiently read Matrix Market format
`fread_rownames()`	Use `fread()` to read a csv/tsv with row names (e.g. one created with `write.table()`)
`fwrite()`	Wrapper for data.table::fwrite with NA's saved as "NA" instad of "".
`fwrite_mm()`	Efficiently write Matrix Market format
`gen_seeds()`	Generate RNG seeds for parallel runs
`ggpreview()`	Plot using preview instead of plotting to X device
`ggrasterize()`	Rasterize ggplot panel area
`gps()`	Get current plot size for jupyter IRKernel
`%cache_df%`	Tries reading a cached dataframe result from the filename on the right side. If the file is missing, generate the dataframe using the function call on the left side and write the result to the file. If "tgutil.cache" option is FALSE, right side would be always recumputed.
`%cache_matrix%`	Tries reading a cached matrix result from the filename on the right side. If the file is missing, generate the matrix using the function call on the left side and write the result to the file. If "tgutil.cache" option is FALSE, right side would be always recumputed.
`%cache_rds%`	Tries reading a cached dataframe result from the filename on the right side. If the file is missing, generate the dataframe using the function call on the left side and write the result to the file. If "tgutil.cache" option is FALSE, right side would be always recumputed.
`%fcache_df%`	cache_df that force recreating the cached file
`%fcache_matrix%`	cache_matrix that force recreating the cached file
`%fcache_rds%`	cache_rds that force recreating the cached file
`load_character()`	Read a character vector from a file created by save_character
`load_dataframe()`	Read a dataframe from a file created by save_dataframe
`load_matrix()`	Read a matrix from a file created by save_matrix
`load_numeric()`	Read a numeric vector from a file created by save_numeric
`num_logical_cores()`	Return the number of the system's logical CPU cores
`num_physical_cores()`	Return the number of the system's physical CPU cores
`pmean()`	Vectorized mean, similiar to `pmin` and `pmax`
`psum()`	Vectorized sum, similiar to `pmin` and `pmax`
`read_fastq()`	Read a fastq file to data frame
`rowMaxs()`	A wrapper for matrixStats::rowMaxs() Returns the maximal numeric value per row in a matrix or a dataframe
`rowMins()`	A wrapper for matrixStats::rowMins() Returns the minimal numeric value per row in a matrix or a dataframe
`run_wide()`	Similar to mclapply, however ensures a reproducible random-number stream for each application of fun()
`save_character()`	Write a character vector to a file, preserving cell names.
`save_dataframe()`	Writes a dataframe to a file, preserving row names.
`save_matrix()`	Writes a matrix to a file, preserving row and column names.
`save_numeric()`	Write a numeric vector to a file, preserving cell names.
`scale_x_log2()`	Scale x axis by log2 (similar to scale_x_log10)
`scale_y_log2()`	Scale y axis by log2 (similar to scale_y_log10)
`segment_by()`	Segment a dataframe according to consecutive identical values of a column expression.
`sps()`	Set plot size for jupyter IRKernel
`tgplot_add_axis_annotation()`	Add an axis annotation to a ggplot matrix
`tgplot_heatmap()`	Easily plot a matrix as an heatmap using ggplot2
`tgutil`	tgutil.
`write_fastq()`	Write a data frame with "id", "seq" and "qual" to fastq file

Reference

All functions