Currently supports ortholog mapping between any
pair of 700+ species.
Use map_species to
return a full list of available organisms.
convert_orthologs(
gene_df,
gene_input = "rownames",
gene_output = "rownames",
standardise_genes = FALSE,
input_species,
output_species = "human",
method = c("gprofiler", "homologene", "babelgene"),
drop_nonorths = TRUE,
non121_strategy = "drop_both_species",
agg_fun = NULL,
mthreshold = Inf,
as_sparse = FALSE,
as_DelayedArray = FALSE,
sort_rows = FALSE,
gene_map = NULL,
input_col = "input_gene",
output_col = "ortholog_gene",
verbose = TRUE,
...
)Data object containing the genes
(see gene_input for options on how
the genes can be stored within the object).
Can be one of the following formats:
matrixA sparse or dense matrix.
data.frameA data.frame,
data.table. or tibble.
listA list or character vector.
Genes, transcripts, proteins, SNPs, or genomic ranges
can be provided in any format
(HGNC, Ensembl, RefSeq, UniProt, etc.) and will be
automatically converted to gene symbols unless
specified otherwise with the ... arguments.
Note: If you set method="homologene", you
must either supply genes in gene symbol format (e.g. "Sox2")
OR set standardise_genes=TRUE.
Which aspect of gene_df to
get gene names from:
"rownames"From row names of data.frame/matrix.
"colnames"From column names of data.frame/matrix.
<column name>From a column in gene_df,
e.g. "gene_names".
How to return genes.
Options include:
"rownames"As row names of gene_df.
"colnames"As column names of gene_df.
"columns"As new columns "input_gene", "ortholog_gene"
(and "input_gene_standard" if standardise_genes=TRUE)
in gene_df.
"dict"As a dictionary (named list) where the names are input_gene and the values are ortholog_gene.
"dict_rev"As a reversed dictionary (named list) where the names are ortholog_gene and the values are input_gene.
If TRUE AND
gene_output="columns", a new column "input_gene_standard"
will be added to gene_df containing standardised HGNC symbols
identified by gorth.
Name of the input species (e.g., "mouse","fly"). Use map_species to return a full list of available species.
Name of the output species (e.g. "human","chicken"). Use map_species to return a full list of available species.
R package to use for gene mapping:
"gprofiler"Slower but more species and genes.
"homologene"Faster but fewer species and genes.
"babelgene"Faster but fewer species and genes. Also gives consensus scores for each gene mapping based on a several different data sources.
Drop genes that don't have an ortholog
in the output_species.
How to handle genes that don't have
1:1 mappings between input_species:output_species.
Options include:
"drop_both_species" or "dbs" or 1Drop genes that have duplicate
mappings in either the input_species or output_species
(DEFAULT).
"drop_input_species" or "dis" or 2Only drop genes that have duplicate
mappings in the input_species.
"drop_output_species" or "dos" or 3Only drop genes that have duplicate
mappings in the output_species.
"keep_both_species" or "kbs" or 4Keep all genes regardless of whether they have duplicate mappings in either species.
"keep_popular" or "kp" or 5Return only the most "popular" interspecies ortholog mappings. This procedure tends to yield a greater number of returned genes but at the cost of many of them not being true biological 1:1 orthologs.
"sum","mean","median","min" or "max"When gene_df is a matrix and gene_output="rownames",
these options will aggregate many-to-one gene mappings
(input_species-to-output_species)
after dropping any duplicate genes in the output_species.
Aggregation function passed to
aggregate_mapped_genes.
Set to NULL to skip aggregation step (default).
Maximum number of ortholog names per gene to show.
Passed to gorth.
Only used when method="gprofiler" (DEFAULT : Inf).
Convert gene_df to a sparse matrix.
Only works if gene_df is one of the following classes:
matrix
Matrix
data.frame
data.table
tibble
If gene_df is a sparse matrix to begin with,
it will be returned as a sparse matrix
(so long as gene_output= "rownames" or "colnames").
Convert aggregated matrix to DelayedArray.
Sort gene_df rows alphanumerically.
A data.frame that maps the current gene names to new gene names. This function's behaviour will adapt to different situations as follows:
gene_map=<data.frame>When a data.frame containing the
gene key:value columns
(specified by input_col and output_col, respectively)
is provided, this will be used to perform aggregation/expansion.
gene_map=NULL and input_species!=output_speciesA gene_map is automatically generated by
map_orthologs to perform inter-species
gene aggregation/expansion.
gene_map=NULL and input_species==output_speciesA gene_map is automatically generated by
map_genes to perform within-species
gene gene symbol standardization and aggregation/expansion.
Column name within gene_map with gene names matching
the row names of X.
Column name within gene_map with gene names
that you wish you map the row names of X onto.
Print messages.
Additional arguments to be passed to
gorth or homologene.
NOTE: To return only the most "popular"
interspecies ortholog mappings,
supply mthreshold=1 here AND set method="gprofiler" above.
This procedure tends to yield a greater number of returned genes but at
the cost of many of them not being true biological 1:1 orthologs.
For more details, please see
here.
gene_df with orthologs converted to the
output_species.
Instead returned as a dictionary (named list) if
gene_output="dict" or "dict_rev".
data("exp_mouse")
gene_df <- convert_orthologs(
gene_df = exp_mouse,
input_species = "mouse"
)
#> Preparing gene_df.
#> sparseMatrix format detected.
#> Extracting genes from rownames.
#> 15,259 genes extracted.
#> Converting mouse ==> human orthologs using: gprofiler
#> Retrieving all organisms available in gprofiler.
#> Using stored `gprofiler_orgs`.
#> Mapping species name: mouse
#> Common name mapping found for mouse
#> 1 organism identified from search: mmusculus
#> Retrieving all organisms available in gprofiler.
#> Using stored `gprofiler_orgs`.
#> Mapping species name: human
#> Common name mapping found for human
#> 1 organism identified from search: hsapiens
#> Checking for genes without orthologs in human.
#> Extracting genes from input_gene.
#> 15,690 genes extracted.
#> Extracting genes from ortholog_gene.
#> 15,690 genes extracted.
#> Dropping 2,674 NAs of all kinds from ortholog_gene.
#> Checking for genes without 1:1 orthologs.
#> Dropping 272 genes that have multiple input_gene per ortholog_gene (many:1).
#> Dropping 202 genes that have multiple ortholog_gene per input_gene (1:many).
#> Filtering gene_df with gene_map
#> Setting ortholog_gene to rownames.
#>
#> =========== REPORT SUMMARY ===========
#> Total genes dropped after convert_orthologs :
#> 2,960 / 15,259 (19%)
#> Total genes remaining after convert_orthologs :
#> 12,299 / 15,259 (81%)