tissue_classifer: Classify genetic signals using a simple rule-based classifier
In Jmtorres138/TACTICAL: What the package does (One Line, Title Case)

This function takes the calculated toa scores for each genetic signal and applies a simple rule-based classifier to assign each signal to a tissue/cell-type. The signal is assigned to the tissue/cell-type that has the highest TOA score and exceeds a user-specified score threshold (default 0.2). The user can also specify a threshold for determining shared signals. If two or more tissues yield TOA scores that fall within this specified range of each other, the signal is designated as a "shared" signal. If designated as shared, the responsible tissues will be indicated in the output data frame.

1	tissue_classifer(toa.df, tissue_threshold = 0.2, shared_threshold = 0.1)

`toa.df`	Dataframe of tissue scores for each SNP (output from calculate_tissue_vectors function)
`tissue_threshold`	Dataframe of tissue scores for each SNP (output from calculate_tissue_vectors function)
`shared_threshold`	Dataframe of tissue scores for each SNP (output from calculate_tissue_vectors function)