Wrangle and Analyze Growth Curve Data
Make design pattern
Calculate area under the curve
Turn tidydesign into block format
Calculate derivatives of vector of data
Calculate centroid
Calculate doubling time equivalent of per-capita growth rate
Extract parts of an object
Calculate lag time
Find local extrema of a numeric vector
Find the first local maxima of a numeric vector
A function that converts base-26 Excel-style letters to numbers
Fit a Smoothing Spline
Import blockdesigns
Import blockmeasures
Make design data.frame(s)
Create R objects or files as seen in vignette examples
Make tidy design data.frames
Create method argument for train of growth curve smoothers
Collapse a list of dataframes, or merge two dataframes together
Maxima and Minima
Moving window smoothing
Paste a list of blocks into a single block
Predict data by linear interpolation from existing data
Nicely print the contents of a data.frame
Read blocks
Read tidy-shaped files
Read wides
Separate a column into multiple columns
Smooth data
Return missing information about a line
Find point(s) when a numeric vector crosses some threshold
A function that converts numbers into base-26 Excel-style letters
Test efficacy of different smoothing parameters
Transform blocks to wides
Pivot widemeasures longer
Uninterleave list
Where is the Min() or Max() or first TRUE or FALSE?
Write block designs to csv
Easy wrangling and model-free analysis of microbial growth curve data, as commonly output by plate readers. Tools for reshaping common plate reader outputs into 'tidy' formats and merging them with design information, making data easy to work with using 'gcplyr' and other packages. Also streamlines common growth curve processing steps, like smoothing and calculating derivatives, and facilitates model-free characterization and analysis of growth data. See methods at <https://mikeblazanin.github.io/gcplyr/>.