Package {EnrichIntersect}

EnrichIntersect: Enrichment Analysis and Intersecting Sankey Diagram

Description

A flexible tool for enrichment analysis based on user-defined sets. It allows users to perform over-representation analysis of the custom sets among any specified ranked feature list, hence making enrichment analysis applicable to various types of data from different scientific fields. 'EnrichIntersect' also enables an interactive means to visualize identified associations based on, for example, the mix-lasso model (Zhao et al., 2022 doi:10.1016/j.isci.2022.104767) or similar methods.

Author(s)

Maintainer: Zhi Zhao zhi.zhao@medisin.uio.no

Authors:

• Zhi Zhao zhi.zhao@medisin.uio.no

• Manuela Zucknick manuela.zucknick@medisin.uio.no

Other contributors:

• Tero Aittokallio t.a.aittokallio@medisin.uio.no [contributor]

See Also

Useful links:

• https://github.com/ocbe-uio/EnrichIntersect

• Report bugs at https://github.com/ocbe-uio/EnrichIntersect/issues

Data set 'cancers_drug_groups'

Description

Data set 'cancers_drug_groups' is a list including a score dataframe with 147 drugs as rows and 19 cancer types as columns, and a dataframe with 9 self-defined drug groups (1st column) of the 147 drugs (2nd column). More details of the data can be found in the results of paper 'Tissue-specific identification of multi-omics features for pan-cancer drug response prediction' by Zhao Z., Wang S. Zucknick M. and Aittokallio T. (2022).

Usage

cancers_drug_groups

Format

An object of class list of length 2.

Value

No return value.

References

Zhao Z, Wang S, Zucknick M and Aittokallio T (2022). Tissue-specific identification of multi-omics features for pan-cancer drug response prediction. iScience, 25(8): 104767.

Examples

# Load data
data(cancers_drug_groups, package = "EnrichIntersect")

Data set 'cancers_genes_drugs'

Description

Data set 'cancers_genes_drugs' is an array with association scores between 56 genes (1st dimension), three cancer types (2nd dimension) and two drugs (3rd dimension). More details of the data can be found in the results of paper 'Tissue-specific identification of multi-omics features for pan-cancer drug response prediction' by Zhao Z., Wang S. Zucknick M. and Aittokallio T. (2022).

Usage

cancers_genes_drugs

Format

An object of class array of dimension 56 x 3 x 2.

Value

No return value.

References

Zhao Z, Wang S, Zucknick M and Aittokallio T (2022). Tissue-specific identification of multi-omics features for pan-cancer drug response prediction. iScience, 25(8): 104767.

Examples

# Load data
data(cancers_genes_drugs, package = "EnrichIntersect")

Plot enrichment map

Description

Plot enrichment map through a vector or matrix of scores and a self-defined set that summarizes a few groups of the names of the vector or matrix.

Usage

enrichment(
  x,
  custom.set,
  alpha = 0,
  normalize = TRUE,
  permute.n = 100,
  padj.method = "none",
  pvalue.cutoff = 0.05,
  angle = 45,
  match.feature = c("rownames", "colnames"),
  ...
)

Arguments

Value

A list including S, pvalue, and g.

Plot Sankey diagram for intersecting sets

Description

Plot Sankey diagram for intersecting set through an array

Usage

intersectSankey(
  x,
  out.fig = NULL,
  color = NULL,
  step.names = c("Levels", "Variables", "Tasks"),
  fontSize = c(20, 13, 20),
  nodePadding = 11,
  nodeWidth = 5,
  margin = list(right = 180),
  ...
)

Arguments

Value

An object of a D3 JavaScript intersecting Sankey diagram for visualising associations based on the input array.

Examples

# Data set 'cancers_genes_drugs' is an array with association scores between 56 genes (1st
# dimension), three cancer types (2nd dimension) and two drugs (3rd dimension)
data(cancers_genes_drugs, package = "EnrichIntersect")

intersectSankey(cancers_genes_drugs, step.names = c("Cancers", "Genes", "Drugs"))