TF_Filter | R Documentation |
Network calculated using activity and interaction database. Uses mutual information to find possible interactions and keeps the interactions if they are available in the database. Sign of interaction is assigned based on the correlation between the activities.
TF_Filter(
actMat,
GSDB,
miTh = 0.4,
maxTf = 75,
maxInteractions = 300,
nbins = 16,
miMethod = "2d",
corMethod = "spearman",
useCor = FALSE,
removeSignalling = FALSE,
DPI = FALSE,
nameFile = NULL,
...
)
actMat |
numeric matrix. Matrix containing the activities |
GSDB |
List of list. Gene set database of interactions |
miTh |
numeric. Mutual information threshold |
maxTf |
integer (optional). Default 75. Maximum number of transcription
factors in the network. If |
maxInteractions |
integer (optional). Default 300. Maximum number of interactions in the network. |
nbins |
integer (optional). Number of bins Default 16. |
miMethod |
MI calculation method: "2d": 2D discretization with entropy (default) "1d": 1D discretization with infotheo |
corMethod |
character (optional). Method to compute correlation. |
useCor |
Logical (optional). Whether to use correlation instead of mutual information to find possible interactions. |
removeSignalling |
logical (optional). Whether to remove the Tfs which are not the target of any other Tfs. Default TRUE. It is not recursive and the generated network might still contain some signalling tfs. |
DPI |
logical (optional). Default FALSE. Whether to apply the data processing inequality to remove weak edges from triangles. |
nameFile |
character (optional). Ouput file name. Default NULL (no file output). |
... |
two additional parameters passed from applyDPI (default: miDiff = 0, minMiTh = 0.5) |
data.frame. Contains the interactions in a dataframe listing. source tf, target tf and interaction type (1-activation, 2-inhibition).
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