RVA (version 0.0.5)

plot_gene: Plot gene expression

Description

This is the function to process the gene count table to show gene expression variations over time or across groups.

Usage

plot_gene(
  data = ~dat,
  anno = ~meta,
  gene.names = c("AAAS", "A2ML1", "AADACL3"),
  ct.table.id.type = "ENSEMBL",
  gene.id.type = "SYMBOL",
  treatment = "Treatment",
  sample.id = "sample_id",
  time = "day",
  log.option = TRUE,
  plot.save.to = NULL,
  input.type = "count"
)

Arguments

data

Count table in the format of dataframe with gene id as row.names.

anno

Annotation table that provides design information.

gene.names

Genes to be visualized, in the format of character vector.

ct.table.id.type

The gene id format in data should be one of: ACCNUM, ALIAS, ENSEMBL, ENSEMBLPROT, ENSEMBLTRANS, ENTREZID, ENZYME, EVIDENCE, EVIDENCEALL, GENENAME, GO, GOALL, IPI, MAP, OMIM, ONTOLOGY, ONTOLOGYALL, PATH, PFAM, PMID, PROSITE, REFSEQ, SYMBOL, UCSCKG, UNIGENE, UNIPROT.

gene.id.type

The gene id format of gene.names, should be one of: ACCNUM, ALIAS, ENSEMBL, ENSEMBLPROT, ENSEMBLTRANS, ENTREZID, ENZYME, EVIDENCE, EVIDENCEALL, GENENAME, GO, GOALL, IPI, MAP, OMIM, ONTOLOGY, ONTOLOGYALL, PATH, PFAM, PMID, PROSITE, REFSEQ, SYMBOL, UCSCKG, UNIGENE, UNIPROT.

treatment

The column name to specify treatment groups.

sample.id

The column name to specify sample IDs.

time

The column name to specify different time points.

log.option

Logical option, whether to log2 transform the CPM as y-axis. Default = True.

plot.save.to

The address to save the plot from simplified cutoff combination with FDR of 0.01, 0.05, 0.1, and 0.2.

input.type

One of count or cpm indicating what the input data type is. If count, the CPM of the input data will be calculated using edgeR::cpm(). Default = count.

Value

The function returns a ggplot object.

Details

The function takes the gene counts and returns a ggplot that shows gene expression variation over time or group.

References

Xingpeng Li,Tatiana Gelaf Romer & Aliyah Olaniyan, RVA - RNAseq Visualization Automation tool.

Examples

# NOT RUN {
plot_gene(data = count_table,
anno = sample_annotation)

# }