Downstream analyses - josuebarrera/GenEra GitHub Wiki
GenEra
output
Using Genomic studies
GenEra
can be used for Genomic studies, such as looking at signatures of novelty and conservation along chromosomes (see Manley et al., 2023). Furthermore, the gene age maps ('phylomaps') themselves can inform signatures of molecular novelty during the evolutionary history of given organisms (see Barrera-Redondo et al., 2023).
'Phylomaps' made using GenEra or from previous studies using other tools have been assembled here.
Transcriptomic studies
The myTAI
package aims to provide a standard tool for Evolutionary Transcriptomics studies and relies on gene age estimate tables as input. The output of GenEra
can easily be used for the gene age estimate tables for myTAI
.
# [TAXID] is used in place for the species of interest
[TAXID].data <-readr::read_tsv("[TAXID]_gene_ages.tsv")
[TAXID].PhyloMap <-
dplyr::select(
[TAXID].data,
Phylostratum = rank,
GeneID = `#gene`
)
# Then `myTAI::MatchMap()` can be used to create the PES object for downstream analysis,
# given that the user has a gene expression matrix, i.e. `[TAXID].ExpressionMatrix`
[TAXID].PES <-
myTAI::MatchMap(
[TAXID].PhyloMap,
[TAXID].ExpressionMatrix,
remove.duplicates = FALSE,
accumulate = NULL)
# To plot the TAI pattern
myTAI::PlotSignature(
tidyr::drop_na([TAXID].PES))