Topic 1-09: Gene ID conversion

Zuguang Gu

2025-03-02

Source: vignettes/topic1_09_gene_id.Rmd

Gene ID type conversion is a very common task in gene set enrichment analysis. There are two types of packages for gene ID conversion: biomaRt which uses the Ensembl biomart web service and org.*.db family packages where the source information is from NCBI. Here we only introduce the org.*.db packages because they should be enough in applications.

We take org.Hs.eg.db (for human) as an example.

library(org.Hs.eg.db)
## Loading required package: AnnotationDbi
## Loading required package: stats4
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##     match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
##     Position, rank, rbind, Reduce, rownames, sapply, saveRDS, setdiff,
##     table, tapply, union, unique, unsplit, which.max, which.min
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Note: it is the same for the OrgDb objects for other orgainsms on AnnotationHub.

Use the select() interface

We need the following three types of information:

  • keys: Gene IDs in one ID type;
  • keytypes: The name of the input ID type;
  • columns: The name of the output ID type;

To get the valid name of ID types:

keytypes(org.Hs.eg.db)
##  [1] "ACCNUM"       "ALIAS"        "ENSEMBL"      "ENSEMBLPROT"  "ENSEMBLTRANS"
##  [6] "ENTREZID"     "ENZYME"       "EVIDENCE"     "EVIDENCEALL"  "GENENAME"    
## [11] "GENETYPE"     "GO"           "GOALL"        "IPI"          "MAP"         
## [16] "OMIM"         "ONTOLOGY"     "ONTOLOGYALL"  "PATH"         "PFAM"        
## [21] "PMID"         "PROSITE"      "REFSEQ"       "SYMBOL"       "UCSCKG"      
## [26] "UNIPROT"
columns(org.Hs.eg.db)
##  [1] "ACCNUM"       "ALIAS"        "ENSEMBL"      "ENSEMBLPROT"  "ENSEMBLTRANS"
##  [6] "ENTREZID"     "ENZYME"       "EVIDENCE"     "EVIDENCEALL"  "GENENAME"    
## [11] "GENETYPE"     "GO"           "GOALL"        "IPI"          "MAP"         
## [16] "OMIM"         "ONTOLOGY"     "ONTOLOGYALL"  "PATH"         "PFAM"        
## [21] "PMID"         "PROSITE"      "REFSEQ"       "SYMBOL"       "UCSCKG"      
## [26] "UNIPROT"

1:1 mapping

For example, we want to convert the following two genes into Entrez IDs.

genes = c("TP53", "MDM2")
  1. use select(). The following function call can be read as “select ‘ENTREZID’ for the genes where their ‘SYMBOL’ are in ‘gene’”.
map = select(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", columns = "ENTREZID")
## 'select()' returned 1:1 mapping between keys and columns
map
##   SYMBOL ENTREZID
## 1   TP53     7157
## 2   MDM2     4193

What if we convert them to Ensembl gene IDs:

map = select(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", columns = "ENSEMBL")
## 'select()' returned 1:1 mapping between keys and columns
map
##   SYMBOL         ENSEMBL
## 1   TP53 ENSG00000141510
## 2   MDM2 ENSG00000135679

If you want to map to multiple ID types:

select(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", columns = c("ENTREZID", "ENSEMBL"))
## 'select()' returned 1:1 mapping between keys and columns
##   SYMBOL ENTREZID         ENSEMBL
## 1   TP53     7157 ENSG00000141510
## 2   MDM2     4193 ENSG00000135679
  1. use mapIds() which is very similar to select().

Note the argument is named column instead of columns, so you can only map to one gene ID type.

mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID")
## 'select()' returned 1:1 mapping between keys and columns
##   TP53   MDM2 
## "7157" "4193"
mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENSEMBL")
## 'select()' returned 1:1 mapping between keys and columns
##              TP53              MDM2 
## "ENSG00000141510" "ENSG00000135679"

1:many mapping

Now there might be some problems if the mapping is not 1:1.

genes = c("TP53", "MMD2")
map = select(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", columns = "ENTREZID")
## 'select()' returned 1:many mapping between keys and columns
map
##   SYMBOL  ENTREZID
## 1   TP53      7157
## 2   MMD2    221938
## 3   MMD2 100505381

Usually it is hard to pick one unique gene for such 1:mapping case, but we can add an additional column “GENETYPE” when querying:

map = select(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", columns = c("ENTREZID", "GENETYPE"))
## 'select()' returned 1:many mapping between keys and columns
map
##   SYMBOL  ENTREZID       GENETYPE
## 1   TP53      7157 protein-coding
## 2   MMD2    221938 protein-coding
## 3   MMD2 100505381        unknown

For “MMD2”, adding the “GENETYPE” column works because the second hit of it is annotated to “unknown”. We can simply remove it.

map[map$GENETYPE == "protein-coding", ]
##   SYMBOL ENTREZID       GENETYPE
## 1   TP53     7157 protein-coding
## 2   MMD2   221938 protein-coding

And it is always a good idea to only inlucde protein-coding genes in gene set enrichment analysis.

But for mapIds(), it is not as flexible as select(). The multiVals argument controls how to select the gene when the mapping is not 1-vs-1.

mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID", multiVals = "first")
## 'select()' returned 1:many mapping between keys and columns
##     TP53     MMD2 
##   "7157" "221938"
mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID", multiVals = "asNA")
## 'select()' returned 1:many mapping between keys and columns
##   TP53   MMD2 
## "7157"     NA
mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID", multiVals = "list")
## 'select()' returned 1:many mapping between keys and columns
## $TP53
## [1] "7157"
## 
## $MMD2
## [1] "221938"    "100505381"
mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID", multiVals = "filter")
## 'select()' returned 1:many mapping between keys and columns
##   TP53 
## "7157"
gene_type = as.list(org.Hs.egGENETYPE)
# this is very slow
mapIds(org.Hs.eg.db, keys = genes, keytype = "SYMBOL", column = "ENTREZID", 
    multiVals = function(x) {
        x2 = x[sapply(as.list(gene_type[x]), function(y) y == "protein-coding")]
        if(length(x2)) {
            x2[1]
        } else {
            NA
        }
})
## 'select()' returned 1:many mapping between keys and columns
##     TP53     MMD2 
##   "7157" "221938"

Use the pre-generated objects

In org.*.db, there are also pre-generated objects that already contains mapping between EntreZ IDs to a specific gene ID type.

ls(envir = asNamespace("org.Hs.eg.db"))
##  [1] "datacache"                "org.Hs.eg"               
##  [3] "org.Hs.eg_dbconn"         "org.Hs.eg_dbfile"        
##  [5] "org.Hs.eg_dbInfo"         "org.Hs.eg_dbschema"      
##  [7] "org.Hs.eg.db"             "org.Hs.egACCNUM"         
##  [9] "org.Hs.egACCNUM2EG"       "org.Hs.egALIAS2EG"       
## [11] "org.Hs.egCHR"             "org.Hs.egCHRLENGTHS"     
## [13] "org.Hs.egCHRLOC"          "org.Hs.egCHRLOCEND"      
## [15] "org.Hs.egENSEMBL"         "org.Hs.egENSEMBL2EG"     
## [17] "org.Hs.egENSEMBLPROT"     "org.Hs.egENSEMBLPROT2EG" 
## [19] "org.Hs.egENSEMBLTRANS"    "org.Hs.egENSEMBLTRANS2EG"
## [21] "org.Hs.egENZYME"          "org.Hs.egENZYME2EG"      
## [23] "org.Hs.egGENENAME"        "org.Hs.egGENETYPE"       
## [25] "org.Hs.egGO"              "org.Hs.egGO2ALLEGS"      
## [27] "org.Hs.egGO2EG"           "org.Hs.egMAP"            
## [29] "org.Hs.egMAP2EG"          "org.Hs.egMAPCOUNTS"      
## [31] "org.Hs.egOMIM"            "org.Hs.egOMIM2EG"        
## [33] "org.Hs.egORGANISM"        "org.Hs.egPATH"           
## [35] "org.Hs.egPATH2EG"         "org.Hs.egPFAM"           
## [37] "org.Hs.egPMID"            "org.Hs.egPMID2EG"        
## [39] "org.Hs.egPROSITE"         "org.Hs.egREFSEQ"         
## [41] "org.Hs.egREFSEQ2EG"       "org.Hs.egSYMBOL"         
## [43] "org.Hs.egSYMBOL2EG"       "org.Hs.egUCSCKG"         
## [45] "org.Hs.egUNIPROT"

The following six objects can be used to convert between major gene ID types:

  • org.Hs.egENSEMBL: Entrez -> Ensembl
  • org.Hs.egENSEMBL2EG: Ensembl -> Entrez
  • org.Hs.egREFSEQ: Entrez -> RefSeq
  • org.Hs.egREFSEQ2EG: RefSeq -> Entrez
  • org.Hs.egSYMBOL: Entrez -> Symbol
  • org.Hs.egSYMBOL2EG: Symbol -> Entrez
org.Hs.egSYMBOL
## SYMBOL map for Human (object of class "AnnDbBimap")

If you have a single gene, you can use [[:

org.Hs.egSYMBOL2EG[["TP53"]]
## [1] "7157"

If you have multiple genes, use [ + as.list():

lt = as.list(org.Hs.egSYMBOL2EG)
lt[genes]
## $TP53
## [1] "7157"
## 
## $MMD2
## [1] "221938"    "100505381"
# or
as.list(org.Hs.egSYMBOL2EG[genes])
## $TP53
## [1] "7157"
## 
## $MMD2
## [1] "221938"    "100505381"

You can also use toTable(), but it is less used for converting gene IDs:

tb = toTable(org.Hs.egSYMBOL2EG)

As you can see, the drawback is you cannot use additional information to filter genes, such as gene types.

Conclusion

If the mappig is 1:1, all the methods metioned is OK. When the mapping is 1:many, use select() + filtering by the “GENETYPE” column is safer.

In the GSEAtraining package, there is one such function. It also automatically detect the input gene ID type.

Practice

Practice 1

In the object diff_gene from the following code, there is a vector of gene symbols (human), try to convert them to EntreZ IDs (do not use convert_to_entrez_id()).

lt = readRDS(system.file("extdata", "ora.rds", package = "GSEAtraining"))
diff_gene = lt$diff_gene
head(diff_gene)
## [1] "FGR"    "NIPAL3" "LAP3"   "CASP10" "CAMKK1" "PRSS22"

Solution 

map = select(org.Hs.eg.db, keys = diff_gene, keytype = "SYMBOL", columns = "ENTREZID")
unique(map$ENTREZID)

# or
map = mapIds(org.Hs.eg.db, keys = diff_gene, keytype = "SYMBOL", column = "ENTREZID")

Practice 2

Now we know gene ID mapping between different ID types is not always 1:1. Count how many (the percent) gene symbols can not be uniquely mapped to EntreZ IDs, and how many (the percent) Ensembl IDs can not be uniquely mapped to EntreZ IDs. And recalculate these two numbers only taking into account the protein-coding genes.

Solution 

all_symbols = keys(org.Hs.eg.db, keytype = "SYMBOL")

# use select
map = select(org.Hs.eg.db, keys = all_symbols, keytype = "SYMBOL", columns = "ENTREZID")
## 'select()' returned 1:many mapping between keys and columns
tb = table(map$SYMBOL)
sum(tb > 1)/length(tb)
## [1] 8.799081e-05
# use mapIds
map = mapIds(org.Hs.eg.db, keys = all_symbols, keytype = "SYMBOL", column = "ENTREZID", 
    multiVals = "list")
## 'select()' returned 1:many mapping between keys and columns
n = sapply(map, length)
sum(n > 1)/length(n)
## [1] 8.799081e-05
# use org.Hs.egSYMBOL2EG
lt = as.list(org.Hs.egSYMBOL2EG)
n = sapply(lt, length)
sum(n > 1)/length(n)
## [1] 8.799081e-05

Only protein-coding genes:

# use select
map = select(org.Hs.eg.db, keys = all_symbols, keytype = "SYMBOL", 
    columns = c("ENTREZID", "GENETYPE"))
## 'select()' returned 1:many mapping between keys and columns
map = map[map$GENETYPE == "protein-coding", ]

tb = table(map$SYMBOL)
sum(tb > 1)/length(tb)
## [1] 0

Ensembl -> Entrez

all_ids = keys(org.Hs.eg.db, keytype = "ENSEMBL")

# use select
map = select(org.Hs.eg.db, keys = all_ids, keytype = "ENSEMBL", columns = "ENTREZID")
## 'select()' returned 1:many mapping between keys and columns
tb = table(map$ENSEMBL)
sum(tb > 1)/length(tb)
## [1] 0.01731188
tail(sort(tb))
## 
## ENSG00000276700 ENSG00000277739 ENSG00000278189 ENSG00000278233 ENSG00000288326 
##             208             208             208             208             208 
## ENSG00000288387 
##             208

Only protein-coding genes:

# use select
map = select(org.Hs.eg.db, keys = all_ids, keytype = "ENSEMBL", columns = c("ENTREZID", "GENETYPE"))
## 'select()' returned 1:many mapping between keys and columns
map = map[map$GENETYPE == "protein-coding", ]

tb = table(map$ENSEMBL)
sum(tb > 1)/length(tb)
## [1] 0.01828566

Last, we add a SYMBOL column in the map table and check what are these Ensembl genes which map to so many Entrez genes:

map = select(org.Hs.eg.db, keys = all_ids, keytype = "ENSEMBL", 
    columns = c("ENTREZID", "SYMBOL", "GENETYPE"))
## 'select()' returned 1:many mapping between keys and columns
map[map$ENSEMBL %in% names(tail(sort(tb))), ]
##               ENSEMBL  ENTREZID       SYMBOL       GENETYPE
## 6361  ENSG00000258992      7258        TSPY1 protein-coding
## 6362  ENSG00000258992     64591        TSPY2 protein-coding
## 6363  ENSG00000258992    728137        TSPY3 protein-coding
## 6364  ENSG00000258992    728403        TSPY8 protein-coding
## 6365  ENSG00000258992 124905614 LOC124905614 protein-coding
## 6366  ENSG00000258992 124905615 LOC124905615 protein-coding
## 6367  ENSG00000258992 124905616 LOC124905616 protein-coding
## 6368  ENSG00000258992 124905617 LOC124905617 protein-coding
## 6369  ENSG00000258992 124905618 LOC124905618 protein-coding
## 6370  ENSG00000258992 124905619 LOC124905619 protein-coding
## 6371  ENSG00000258992 124905620 LOC124905620 protein-coding
## 6372  ENSG00000258992 124905621 LOC124905621 protein-coding
## 6373  ENSG00000258992 124905623 LOC124905623 protein-coding
## 6374  ENSG00000258992 124905624 LOC124905624 protein-coding
## 6375  ENSG00000258992 124905625 LOC124905625 protein-coding
## 6376  ENSG00000258992 124905626 LOC124905626 protein-coding
## 6377  ENSG00000258992 124905627 LOC124905627 protein-coding
## 6378  ENSG00000258992 124905628 LOC124905628 protein-coding
## 6379  ENSG00000258992 124905629 LOC124905629 protein-coding
## 6380  ENSG00000258992 124908978 LOC124908978 protein-coding
## 6381  ENSG00000258992 124908979 LOC124908979 protein-coding
## 6382  ENSG00000258992 124908980 LOC124908980 protein-coding
## 6383  ENSG00000258992 124908981 LOC124908981 protein-coding
## 6384  ENSG00000258992 124908988 LOC124908988 protein-coding
## 6385  ENSG00000258992 124909015 LOC124909015 protein-coding
## 6386  ENSG00000258992 124909084 LOC124909084 protein-coding
## 6387  ENSG00000258992 124909294 LOC124909294 protein-coding
## 6388  ENSG00000258992 124909306 LOC124909306 protein-coding
## 6389  ENSG00000258992 124909318 LOC124909318 protein-coding
## 6390  ENSG00000258992 124909320 LOC124909320 protein-coding
## 6391  ENSG00000258992 124909330 LOC124909330 protein-coding
## 6392  ENSG00000258992 128966595 LOC128966595 protein-coding
## 6393  ENSG00000258992 128966599 LOC128966599 protein-coding
## 6394  ENSG00000258992 128966647 LOC128966647 protein-coding
## 6395  ENSG00000258992 128966655 LOC128966655 protein-coding
## 6396  ENSG00000258992 128966656 LOC128966656 protein-coding
## 26612 ENSG00000284234    646066      TAF11L5 protein-coding
## 26613 ENSG00000284234 124906475 LOC124906475 protein-coding
## 26614 ENSG00000284234 124906476 LOC124906476 protein-coding
## 26615 ENSG00000284234 124906477 LOC124906477 protein-coding
## 26616 ENSG00000284234 124906478 LOC124906478 protein-coding
## 26617 ENSG00000284234 124906479 LOC124906479 protein-coding
## 26618 ENSG00000284234 124906480 LOC124906480 protein-coding
## 26619 ENSG00000284234 124906481 LOC124906481 protein-coding
## 26620 ENSG00000284234 124906482 LOC124906482 protein-coding
## 26621 ENSG00000284234 124906483 LOC124906483 protein-coding
## 26622 ENSG00000284234 124906484 LOC124906484 protein-coding
## 26623 ENSG00000284234 124906485 LOC124906485 protein-coding
## 26624 ENSG00000284234 124906486 LOC124906486 protein-coding
## 26625 ENSG00000284234 124906487 LOC124906487 protein-coding
## 26626 ENSG00000284234 124906488 LOC124906488 protein-coding
## 26627 ENSG00000284234 124906489 LOC124906489 protein-coding
## 26628 ENSG00000284234 124906490 LOC124906490 protein-coding
## 26629 ENSG00000284234 124906491 LOC124906491 protein-coding
## 26630 ENSG00000284234 128966665 LOC128966665 protein-coding
## 26631 ENSG00000284234 128966671 LOC128966671 protein-coding
## 26632 ENSG00000284234 128966672 LOC128966672 protein-coding
## 26633 ENSG00000284234 128966673 LOC128966673 protein-coding
## 26634 ENSG00000284234 130160542 LOC130160542 protein-coding
## 26635 ENSG00000284234 130160543 LOC130160543 protein-coding
## 26636 ENSG00000284234 130160544 LOC130160544 protein-coding
## 26637 ENSG00000284234 130160545 LOC130160545 protein-coding
## 26638 ENSG00000284234 130160546 LOC130160546 protein-coding
## 26639 ENSG00000284234 130160547 LOC130160547 protein-coding
## 26640 ENSG00000284234 130160548 LOC130160548 protein-coding
## 26641 ENSG00000284234 130160549 LOC130160549 protein-coding
## 27433 ENSG00000228927    728137        TSPY3 protein-coding
## 27434 ENSG00000228927 100289087       TSPY10 protein-coding
## 27435 ENSG00000228927 124905614 LOC124905614 protein-coding
## 27436 ENSG00000228927 124905615 LOC124905615 protein-coding
## 27437 ENSG00000228927 124905616 LOC124905616 protein-coding
## 27438 ENSG00000228927 124905617 LOC124905617 protein-coding
## 27439 ENSG00000228927 124905618 LOC124905618 protein-coding
## 27440 ENSG00000228927 124905619 LOC124905619 protein-coding
## 27441 ENSG00000228927 124905620 LOC124905620 protein-coding
## 27442 ENSG00000228927 124905621 LOC124905621 protein-coding
## 27443 ENSG00000228927 124905624 LOC124905624 protein-coding
## 27444 ENSG00000228927 124905625 LOC124905625 protein-coding
## 27445 ENSG00000228927 124905626 LOC124905626 protein-coding
## 27446 ENSG00000228927 124905627 LOC124905627 protein-coding
## 27447 ENSG00000228927 124905628 LOC124905628 protein-coding
## 27448 ENSG00000228927 124905629 LOC124905629 protein-coding
## 27449 ENSG00000228927 124908978 LOC124908978 protein-coding
## 27450 ENSG00000228927 124908979 LOC124908979 protein-coding
## 27451 ENSG00000228927 124908980 LOC124908980 protein-coding
## 27452 ENSG00000228927 124908981 LOC124908981 protein-coding
## 27453 ENSG00000228927 124909197 LOC124909197 protein-coding
## 27454 ENSG00000228927 124909294 LOC124909294 protein-coding
## 27455 ENSG00000228927 124909306 LOC124909306 protein-coding
## 27456 ENSG00000228927 124909318 LOC124909318 protein-coding
## 27457 ENSG00000228927 124909320 LOC124909320 protein-coding
## 27458 ENSG00000228927 124909330 LOC124909330 protein-coding
## 27459 ENSG00000228927 128966595 LOC128966595 protein-coding
## 27460 ENSG00000228927 128966599 LOC128966599 protein-coding
## 27461 ENSG00000228927 128966647 LOC128966647 protein-coding
## 27462 ENSG00000228927 128966655 LOC128966655 protein-coding
## 27463 ENSG00000236424    728137        TSPY3 protein-coding
## 27464 ENSG00000236424 100289087       TSPY10 protein-coding
## 27465 ENSG00000236424 124905614 LOC124905614 protein-coding
## 27466 ENSG00000236424 124905615 LOC124905615 protein-coding
## 27467 ENSG00000236424 124905616 LOC124905616 protein-coding
## 27468 ENSG00000236424 124905617 LOC124905617 protein-coding
## 27469 ENSG00000236424 124905618 LOC124905618 protein-coding
## 27470 ENSG00000236424 124905619 LOC124905619 protein-coding
## 27471 ENSG00000236424 124905620 LOC124905620 protein-coding
## 27472 ENSG00000236424 124905621 LOC124905621 protein-coding
## 27473 ENSG00000236424 124905624 LOC124905624 protein-coding
## 27474 ENSG00000236424 124905625 LOC124905625 protein-coding
## 27475 ENSG00000236424 124905626 LOC124905626 protein-coding
## 27476 ENSG00000236424 124905627 LOC124905627 protein-coding
## 27477 ENSG00000236424 124905628 LOC124905628 protein-coding
## 27478 ENSG00000236424 124905629 LOC124905629 protein-coding
## 27479 ENSG00000236424 124908978 LOC124908978 protein-coding
## 27480 ENSG00000236424 124908979 LOC124908979 protein-coding
## 27481 ENSG00000236424 124908980 LOC124908980 protein-coding
## 27482 ENSG00000236424 124908981 LOC124908981 protein-coding
## 27483 ENSG00000236424 124909093 LOC124909093 protein-coding
## 27484 ENSG00000236424 124909197 LOC124909197 protein-coding
## 27485 ENSG00000236424 124909294 LOC124909294 protein-coding
## 27486 ENSG00000236424 124909306 LOC124909306 protein-coding
## 27487 ENSG00000236424 124909318 LOC124909318 protein-coding
## 27488 ENSG00000236424 128966595 LOC128966595 protein-coding
## 27489 ENSG00000236424 128966599 LOC128966599 protein-coding
## 27490 ENSG00000236424 128966647 LOC128966647 protein-coding
## 27491 ENSG00000236424 128966655 LOC128966655 protein-coding
## 27692 ENSG00000292275    728753     FAM90A19 protein-coding
## 27693 ENSG00000292275 124906721 LOC124906721 protein-coding
## 27694 ENSG00000292275 124906751 LOC124906751 protein-coding
## 27695 ENSG00000292275 124906752 LOC124906752 protein-coding
## 27696 ENSG00000292275 124906754 LOC124906754 protein-coding
## 27697 ENSG00000292275 124906756 LOC124906756 protein-coding
## 27698 ENSG00000292275 124906758 LOC124906758 protein-coding
## 27699 ENSG00000292275 124906759 LOC124906759 protein-coding
## 27700 ENSG00000292275 124906760 LOC124906760 protein-coding
## 27701 ENSG00000292275 124906763 LOC124906763 protein-coding
## 27702 ENSG00000292275 124906764 LOC124906764 protein-coding
## 27703 ENSG00000292275 124906767 LOC124906767 protein-coding
## 27704 ENSG00000292275 128966593 LOC128966593 protein-coding
## 27705 ENSG00000292275 128966604 LOC128966604 protein-coding
## 27706 ENSG00000292275 128966605 LOC128966605 protein-coding
## 27707 ENSG00000292275 130160541 LOC130160541 protein-coding
## 44024 ENSG00000284356 112488738     TAF11L10 protein-coding
## 44025 ENSG00000284356 124906475 LOC124906475 protein-coding
## 44026 ENSG00000284356 124906476 LOC124906476 protein-coding
## 44027 ENSG00000284356 124906477 LOC124906477 protein-coding
## 44028 ENSG00000284356 124906478 LOC124906478 protein-coding
## 44029 ENSG00000284356 124906479 LOC124906479 protein-coding
## 44030 ENSG00000284356 124906480 LOC124906480 protein-coding
## 44031 ENSG00000284356 124906481 LOC124906481 protein-coding
## 44032 ENSG00000284356 124906482 LOC124906482 protein-coding
## 44033 ENSG00000284356 124906483 LOC124906483 protein-coding
## 44034 ENSG00000284356 124906484 LOC124906484 protein-coding
## 44035 ENSG00000284356 124906485 LOC124906485 protein-coding
## 44036 ENSG00000284356 124906486 LOC124906486 protein-coding
## 44037 ENSG00000284356 124906487 LOC124906487 protein-coding
## 44038 ENSG00000284356 124906488 LOC124906488 protein-coding
## 44039 ENSG00000284356 124906489 LOC124906489 protein-coding
## 44040 ENSG00000284356 124906490 LOC124906490 protein-coding
## 44041 ENSG00000284356 124906491 LOC124906491 protein-coding
## 44042 ENSG00000284356 128966665 LOC128966665 protein-coding
## 44043 ENSG00000284356 128966671 LOC128966671 protein-coding
## 44044 ENSG00000284356 128966672 LOC128966672 protein-coding
## 44045 ENSG00000284356 128966673 LOC128966673 protein-coding
## 44046 ENSG00000284356 130160542 LOC130160542 protein-coding
## 44047 ENSG00000284356 130160543 LOC130160543 protein-coding
## 44048 ENSG00000284356 130160544 LOC130160544 protein-coding
## 44049 ENSG00000284356 130160545 LOC130160545 protein-coding
## 44050 ENSG00000284356 130160546 LOC130160546 protein-coding
## 44051 ENSG00000284356 130160547 LOC130160547 protein-coding
## 44052 ENSG00000284356 130160548 LOC130160548 protein-coding
## 44053 ENSG00000284356 130160549 LOC130160549 protein-coding