GSNA (version 0.1.4.2)

gsnSubnetSummary: gsnSubnetSummary

Description

Generates a table summarizing subnets that incorporates subnets and pathways data.

Usage

gsnSubnetSummary(
  object,
  pathways.data = NULL,
  distance = NULL,
  id_col = NULL,
  stat_col = NULL,
  sig_order = NULL,
  stat_col_2 = NULL,
  sig_order_2 = NULL,
  summary_statistics = c("hm", "min_max"),
  seed_gs_fields = NULL
)

Value

A data.frame with a statistical summary of subnets.

Arguments

object

A GSNData data object containing a distance matrix and subnets data. If pathways data is not specified by the pathways.data argument (described below), the object must contain imported pathways data as well.

pathways.data

An (optional) data.frame containing pathways data (GSEA, CERNO, GSNORA, etc.) with 1 or 2 associated statistical columns, typically P-values, specified by stat_col and stat_col_2 below.

distance

A distance metric with associated subnets data.

id_col

(optional) This is the name of the column in the pathways data.frame that corresponds to the names of gene sets. The default value is specified by object$pathways$id_col. (See details.)

stat_col

(optional) Specifies the name of the first statistical column, if not specified, defaults to the value in object$pathways$stat_col.

sig_order

(optional) This indicates the behavior of stat_col, whether low values ('loToHi') or high values ('hiToLo') are most significant. The default value is specified in object$pathways$sig_order.

stat_col_2

(optional) Specifies the name of the second statistical column, if not specified, defaults to the value in object$pathways$stat_col_2.

sig_order_2

(optional) This indicates the behavior of stat_col_2, whether low values ('loToHi') or high values ('hiToLo') are most significant. The default value is specified in object$pathways$sig_order_2.

summary_statistics

(optional) A character vector specifying which summary statistics are to be calculated from the 'stat_col'. Acceptable values include 'hm' specifying harmonic mean, 'min_max', specifying either minimum or maximum depending on sig_order, or the name of a function. (default: c('hm', 'min_max'))

seed_gs_fields

(optional) A character vector specifying the names of additional seed gene set fields to retain from pathways data.

Details

The output data.frame contains a list of subnets, each with an associated list of gene set IDs. For each subnet, summary statistics are calculated, including the harmonic mean of stat_col and (if specified) stat_col_2. In addition, the minimum or maximum of the stat_col and stat_col_2 is calculated, depending on the sig_order and sig_order_2. For loToHi, the minimum is calculated, and for hiToLo, the maximum.

Examples

library(GSNA)

# In this example, we generate a gene set network from CERNO example
# data. We begin by subsetting the CERNO data for significant results:
sig_pathways.cerno <- subset( Bai_CiHep_DN.cerno, adj.P.Val <= 0.05 )

# Now create a gene set collection containing just the gene sets
# with significant CERNO results, by subsetting Bai_gsc.tmod using
# the gene set IDs as keys:
sig_pathways.tmod <- Bai_gsc.tmod[sig_pathways.cerno$ID]

# And obtain a background gene set from differential expression data:
background_genes <- toupper( rownames( Bai_CiHep_v_Fib2.de ) )

# Build a gene set network:
sig_pathways.GSN <-
   buildGeneSetNetworkJaccard(geneSetCollection = sig_pathways.tmod,
                              ref.background = background_genes )

# Now import the CERNO data:
sig_pathways.GSN <- gsnImportCERNO( sig_pathways.GSN,
                                    pathways_data = sig_pathways.cerno )

# Now we can pare the network and assign subnets:
sig_pathways.GSN <- gsnPareNetGenericHierarchic( object = sig_pathways.GSN )
sig_pathways.GSN <- gsnAssignSubnets(  object = sig_pathways.GSN )

# Now, get a statistacal summary of the subnets:
gsnSubnetSummary( sig_pathways.GSN )