View source: R/graph_GOspecies.R
graphGOspecies | R Documentation |
graphGOspecies is a function to create undirected graphs using two options: \loadmathjax
Categories option:
The nodes \mjseqn(V) represent groups of gene lists (categories), and the edges \mjseqn(E) represent GO terms co-occurring between pairs of categories. More specifically, Two categories: \mjseqnu,v \epsilon V are connected by an edge \mjseqne=(u,v).the edge weights \mjseqnw(e) are defined as the ratio of the number of GO terms co-occurring between two categories. Edge weights w(e) are defined as the ratio of the number of GO terms (e.g. biological processes) co-occurring between two categories \mjseqnBP_u \ n BP_v compared to the total number of GO terms available. A node weight \mjseqnK_w(u) is defined as the sum of the edge weights where the node u is a participant. Thus, the node weight represents how frequently GO terms are reported and expressed in a biological phenomenon.
\mjsdeqnw(e) = \frac\mid BP_u n BP_v\mid\mid BP\mid (1)
\mjsdeqnK_w = \sum_v \epsilon Vw(u,v) (2)
GO option:
The nodes \mjseqnV represent GO terms and the edges \mjseqnE' represent categories where a pair of GO terms co-occur. More specifically, two GO terms are connected by an edge \mjseqne'=(u,v'). the edge weight \mjseqnw'(e') corresponds to the number of categories co-occurring the GO terms \mjseqnu and \mjseqnv',compared with the total number of GO terms (Equation 3). A node weight \mjseqnK'_w(u') is defined,in this case the weight represents the importance of a GO term (more frequent co-occurring).(Please be patient, it requires a long time to finish).
\mjsdeqnw'(e')=\frac\midCu'\cap Cv'\mid\mid BP \mid (3)
\mjsdeqnK'_w(u')=\sum_v'\epsilon V'w'(u',v') (4)
graphGOspecies( df, GOterm_field, option = "Categories", numCores = 2, saveGraph = FALSE, outdir = NULL, filename = NULL )
df |
A data frame with the results of a functional enrichment analysis for a species with an extra column "feature" with the features to be compared |
GOterm_field |
This is a string with the column name of the GO terms (e.g: "Functional.Category") |
option |
(values: "GO" or "Categories"). This option allows create either a graph where nodes are GO terms and edges are features or alternatively a graph where nodes are features and edges are GO terms (default value="Categories") |
numCores |
numeric, Number of cores to use for the process (default value numCores=2). For the example below, only one core will be used |
saveGraph |
logical, if |
outdir |
This parameter will allow save the graph file in a folder described here (e.g: "D:").This parameter only works when saveGraph=TRUE |
filename |
The name of the graph filename to be saved in the outdir detailed by the user.This parameter only works when saveGraph=TRUE |
This function will return a list with two slots: edges and nodes.
(Categories): Edges list columns:
Column | Description |
SOURCE and TARGET | The source and target categories (Nodes in the edge) |
FEATURES_N | The number of GO terms between the categories |
WEIGHT | Edge weight |
FEATURES | GO terms available for both nodes |
Node list columns:
Column | Description |
feature | Category name |
GO_count | GO terms counts for the node |
WEIGHT | Node weight |
(GO):
Edges list columns:
Column | Description |
SOURCE and TARGET | The source and target GO terms (Nodes in the edge) |
FEATURE | The number of Categories where both GO Terms were found |
WEIGHT | Edge weight |
Node list columns:
Column | Description |
GO | GO term node name |
GO_WEIGHT | Node weight |
#Loading example datasets data(H_sapiens_compress) GOterm_field <- "Functional_Category" #Running function x <- graphGOspecies(df=H_sapiens_compress, GOterm_field=GOterm_field, option = "Categories", numCores=1, saveGraph=FALSE, outdir = NULL, filename=NULL)
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