Convert orthologs

convert_orthologs is very flexible with what users can supply as gene_df, and can take a data.frame/data.table/tibble, (sparse) matrix, or list/vector containing genes.

Genes, transcripts, proteins, SNPs, or genomic ranges will be recognised in most formats (HGNC, Ensembl, RefSeq, UniProt, etc.) and can even be a mixture of different formats.

All genes will be mapped to gene symbols, unless specified otherwise with the ... arguments (see ?orthogene::convert_orthologs or here for details).

gene_df <- orthogene::convert_orthologs(gene_df = exp_mouse,
                                        gene_input = "rownames", 
                                        gene_output = "rownames", 
                                        input_species = "mouse",
                                        output_species = "human",
                                        non121_strategy = "drop_both_species",
                                        method = method) 

## Preparing gene_df.

## sparseMatrix format detected.

## Extracting genes from rownames.

## 15,259 genes extracted.

## Converting mouse ==> human orthologs using: homologene

## Retrieving all organisms available in homologene.

## Mapping species name: mouse

## Common name mapping found for mouse

## 1 organism identified from search: 10090

## Retrieving all organisms available in homologene.

## Mapping species name: human

## Common name mapping found for human

## 1 organism identified from search: 9606

## Checking for genes without orthologs in human.

## Extracting genes from input_gene.

## 13,416 genes extracted.

## Extracting genes from ortholog_gene.

## 13,416 genes extracted.

## Checking for genes without 1:1 orthologs.

## Dropping 46 genes that have multiple input_gene per ortholog_gene (many:1).

## Dropping 56 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 :
##    2,016 / 15,259 (13%)

## Total genes remaining after convert_orthologs :
##    13,243 / 15,259 (87%)

knitr::kable(as.matrix(head(gene_df)))

Map species

map_species lets you standardise species names from a wide variety of identifiers (e.g. common name, taxonomy ID, Latin name, partial match).

All exposed orthogene functions (including convert_orthologs) use map_species under the hood, so you don’t have to worry about getting species names exactly right.

You can check the full list of available species by simply running map_species() with no arguments, or checking here.

species <- orthogene::map_species(species = c("human",9544,"mus musculus",
                                              "fruit fly","Celegans"), 
                                  output_format = "scientific_name")

## Retrieving all organisms available in homologene.

## Mapping species name: human

## Common name mapping found for human

## 1 organism identified from search: Homo sapiens

## Mapping species name: 9544

## 1 organism identified from search: Macaca mulatta

## Mapping species name: mus musculus

## 1 organism identified from search: Mus musculus

## Mapping species name: fruit fly

## Common name mapping found for fruit fly

## 1 organism identified from search: Drosophila melanogaster

## Mapping species name: Celegans

## 1 organism identified from search: Caenorhabditis elegans

print(species)

##                     human                      9544              mus musculus 
##            "Homo sapiens"          "Macaca mulatta"            "Mus musculus" 
##                 fruit fly                  Celegans 
## "Drosophila melanogaster"  "Caenorhabditis elegans"

Report orthologs

It may be helpful to know the maximum expected number of orthologous gene mappings from one species to another.

ortholog_report generates a report that tells you this information genome-wide.

orth_zeb <- orthogene::report_orthologs(target_species = "zebrafish",
                                        reference_species = "human",
                                        method_all_genes = method,
                                        method_convert_orthologs = method) 

## Gathering ortholog reports.

## Retrieving all genes using: homologene.

## Retrieving all organisms available in homologene.

## Mapping species name: human

## Common name mapping found for human

## 1 organism identified from search: 9606

## Gene table with 19,129 rows retrieved.

## Returning all 19,129 genes from human.

## Retrieving all genes using: homologene.

## Retrieving all organisms available in homologene.

## Mapping species name: zebrafish

## Common name mapping found for zebrafish

## 1 organism identified from search: 7955

## Gene table with 20,897 rows retrieved.

## Returning all 20,897 genes from zebrafish.

## --
## --

## Preparing gene_df.

## data.frame format detected.

## Extracting genes from Gene.Symbol.

## 20,897 genes extracted.

## Converting zebrafish ==> human orthologs using: homologene

## Retrieving all organisms available in homologene.

## Mapping species name: zebrafish

## Common name mapping found for zebrafish

## 1 organism identified from search: 7955

## Retrieving all organisms available in homologene.

## Mapping species name: human

## Common name mapping found for human

## 1 organism identified from search: 9606

## Checking for genes without orthologs in human.

## Extracting genes from input_gene.

## 14,768 genes extracted.

## Extracting genes from ortholog_gene.

## 14,768 genes extracted.

## Checking for genes without 1:1 orthologs.

## Dropping 46 genes that have multiple input_gene per ortholog_gene (many:1).

## Dropping 2,707 genes that have multiple ortholog_gene per input_gene (1:many).

## Filtering gene_df with gene_map

## Adding input_gene col to gene_df.

## Adding ortholog_gene col to gene_df.

## 
## =========== REPORT SUMMARY ===========

## Total genes dropped after convert_orthologs :
##    10,336 / 20,895 (49%)

## Total genes remaining after convert_orthologs :
##    10,559 / 20,895 (51%)

## --

## 
## =========== REPORT SUMMARY ===========

## 10,557 / 20,895 (50.52%) target_species genes remain after ortholog conversion.

## 10,557 / 19,129 (55.19%) reference_species genes remain after ortholog conversion.

knitr::kable(head(orth_zeb$map))

knitr::kable(orth_zeb$report)

Map genes

map_genes finds matching within-species synonyms across a wide variety of gene naming conventions (HGNC, Ensembl, RefSeq, UniProt, etc.) and returns a table with standardised gene symbols (or whatever output format you prefer).

genes <-  c("Klf4", "Sox2", "TSPAN12","NM_173007","Q8BKT6",9999,
             "ENSMUSG00000012396","ENSMUSG00000074637")
mapped_genes <- orthogene::map_genes(genes = genes,
                                     species = "mouse", 
                                     drop_na = FALSE)

## 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

## 7 / 8 (87.5%) genes mapped.

knitr::kable(head(mapped_genes))

Aggregate mapped genes

aggregate_mapped_genes does the following:

1. Uses map_genes to identify within-species many-to-one gene mappings (e.g. Ensembl transcript IDs ==> gene symbols). Alternatively, can map across species if output from map_orthologs is supplied to gene_map argument (and gene_map_col="ortholog_gene").
   
2. Drops all non-mappable genes.
   
3. Aggregates the values of matrix gene_df using "sum","mean","median","min" or "max".

Note, this only works when the input data (gene_df) is a sparse or dense matrix, and the genes are row names.

data("exp_mouse_enst") 
knitr::kable(tail(as.matrix(exp_mouse_enst)))

exp_agg <- orthogene::aggregate_mapped_genes(gene_df=exp_mouse_enst,
                                             input_species="mouse", 
                                             agg_fun = "sum")

## 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

## 477 / 482 (98.96%) genes mapped.

## Aggregating rows using: monocle3

## Converting obj to sparseMatrix.

## Matrix aggregated:
##   - Input: 482 x 7 
##   - Output: 92 x 7

knitr::kable(tail(as.matrix(exp_agg)))

Get all genes

You can also quickly get all known genes from the genome of a given species with all_genes.

genome_mouse <- orthogene::all_genes(species = "mouse", 
                                     method = method)

## Retrieving all genes using: homologene.

## Retrieving all organisms available in homologene.

## Mapping species name: mouse

## Common name mapping found for mouse

## 1 organism identified from search: 10090

## Gene table with 21,207 rows retrieved.

## Returning all 21,207 genes from mouse.

knitr::kable(head(genome_mouse))