RunClassifier: Run FIT improvement prediction classifier

In RachellyN/FIT: Predicts human disease relevant genes from mouse model gene expression, based on prior mouse and human gene expression comparisons

Description

The SVM classifier predicts whether FIT will be able to improve a specific mouse data.

Usage

RunClassifier(MouseData = NULL, MouseFile = NULL, DataType = NULL,
  qval = 0.1, FC = 0.15, verbose = F)

Arguments

MouseData	The pre-processed mouse dataset, or NULL in case MouseFIle ise given
MouseFile	File name that includes the mouse data (log expression per gene for all disease and control sampels), in CSV format. NULL in case MouseData is given
DataType	Either "microarray" or "rnaseq", depending on the technology by which the data was assayed. NULL if MouseData is given
qval	the q-value cuttoff the user will use to interpret FIT's predictions. (default= 0.1)
FC	the fold-change cuttoff the user will use to interpret FIT's predictions, given as fraction from the top. For example, 0.15 denotes the top 15% of genes with highest fold-change. (default= 0.15)
verbose	A logical value defining whether detialed messages should be printed.

RachellyN/FIT documentation built on May 16, 2019, 6:59 p.m.