Could reproduce certain code, can you help?

[billchenxi]

library(biomaRt)
myMart <- useMart("ensembl", dataset = "hsapiens_gene_ensembl")
ensemblID <- "ENSG00000008130"
unip <- useDataset("uniprot",mart=useMart("unimart"))

interpro <- getBM(attributes=c("interpro_id","go_id"),
                    filters="ensembl_id", values="ENSG00000008130",mart=unip)

Error in useMart("unimart") :
Incorrect BioMart name, use the listMarts function to see which BioMart databases are available

Thanks.

[HajkD]

Hi,

Please note that this package is called biomartr and not biomaRt.
biomartr is designed to extend the biomaRt package and provides a
user-friendly search strategy for retrieving annotation information stored in
the BioMart database.

First, the biomartr package allows you to retrieve the correct
attribute names by typing:

biomartr::organismAttributes("Homo sapiens", topic = "interpro")

name                description               dataset                 mart
<chr>                      <chr>                 <chr>                <chr>
    1                    interpro                Interpro ID hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
2  interpro_short_description Interpro Short Description hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
3        interpro_description       Interpro Description hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
4              interpro_start             Interpro start hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
5                interpro_end               Interpro end hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
6  interpro_short_description InterPro Short Description    hsapiens_gene_vega ENSEMBL_MART_ENSEMBL
7                    interpro                Interpro ID    hsapiens_gene_vega ENSEMBL_MART_ENSEMBL
8        interpro_description       InterPro Description    hsapiens_gene_vega ENSEMBL_MART_ENSEMBL
9              interpro_start             Interpro start    hsapiens_gene_vega ENSEMBL_MART_ENSEMBL
10               interpro_end               Interpro end    hsapiens_gene_vega ENSEMBL_MART_ENSEMBL
# ... with 40 more rows

As you will observe, in line 7 the attribute for the Interpro ID is named interpro
and not interpro_id as specified by you.

Whereas the attribute go_id is absolutely correct:

biomartr::organismAttributes("Homo sapiens", topic = "go")

name                                  description               dataset                 mart
<chr>                                        <chr>                 <chr>                <chr>
    1                            go_id                            GO Term Accession hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
2                  go_linkage_type                        GO Term Evidence Code hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
3             goslim_goa_accession                      GOSlim GOA Accession(s) hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
4           goslim_goa_description                       GOSlim GOA Description hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
5         vpacos_homolog_goc_score         Alpaca Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
6       pformosa_homolog_goc_score   Amazon molly Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
7  acarolinensis_homolog_goc_score   Anole lizard Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
8  dnovemcinctus_homolog_goc_score      Armadillo Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
9     ogarnettii_homolog_goc_score       Bushbaby Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
10 cintestinalis_homolog_goc_score C.intestinalis Gene-order conservation score hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
# ... with 435 more rows

The biomartr function organismFilters() will now allow you to retrieve the
correct filter name for your query:

biomartr::organismFilters("Homo sapiens", topic = "ensembl")

name                                                  description                       dataset                 mart
<chr>                                                        <chr>                         <chr>                <chr>
    1        with_ox_clone_based_ensembl_gene                          with clone based Ensembl gene ID(s)         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
2  with_ox_clone_based_ensembl_transcript                    with clone based Ensembl transcript ID(s)         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
3                         ensembl_gene_id                            Gene ID(s) [e.g. ENSG00000139618]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
4                   ensembl_transcript_id                      Transcript ID(s) [e.g. ENST00000380152]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
5                      ensembl_peptide_id                         Protein ID(s) [e.g. ENSP00000369497]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
6                         ensembl_exon_id                            Exon ID(s) [e.g. ENSE00001508081]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
7           clone_based_ensembl_gene_name           Clone based Ensembl gene name(s) [e.g. AL162430.1]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
8     clone_based_ensembl_transcript_name Clone based Ensembl transcript name(s) [e.g. AL162430.1-201]         hsapiens_gene_ensembl ENSEMBL_MART_ENSEMBL
9                            ensembl_gene                                  Gene stable ID(s) [Max 500]                  hsapiens_snp ENSEMBL_MART_ENSEMBL
10                        ensembl_gene_id  Ensembl Gene ID(s) (e.g. ENSG00000210049) [Max 500 advised] hsapiens_mirna_target_feature ENSEMBL_MART_ENSEMBL
# ... with 40 more rows

Thus, as stated in line 3 the correct filter name for the ensembl ID is ensembl_gene_id
and not ensembl_id.

Finally, you can use the getMarts() function of biomartr to see available marts for Homo sapiens:

biomartr::getMarts()

                  mart               version
1  ENSEMBL_MART_ENSEMBL      Ensembl Genes 87
2    ENSEMBL_MART_MOUSE      Mouse strains 87
3 ENSEMBL_MART_SEQUENCE              Sequence
4 ENSEMBL_MART_ONTOLOGY              Ontology
5  ENSEMBL_MART_GENOMIC   Genomic features 87
6      ENSEMBL_MART_SNP  Ensembl Variation 87
7  ENSEMBL_MART_FUNCGEN Ensembl Regulation 87
8     ENSEMBL_MART_VEGA               Vega 67

As you can see, when retrieving information for genes the ENSEMBL_MART_ENSEMBL
mart covers Ensembl Genes 87.

When you now run the biomart() function of the biomartr package you will
retrieve all results:

biomartr::biomart(genes = "ENSG00000008130",
                  mart = "ENSEMBL_MART_ENSEMBL",
                  dataset = "hsapiens_gene_ensembl",
                  attributes = c("interpro","go_id"),
                  filters = "ensembl_gene_id"
                  )

ensembl_gene_id  interpro      go_id
1  ENSG00000008130 IPR002504 GO:0005829
2  ENSG00000008130 IPR002504 GO:0046034
3  ENSG00000008130 IPR002504 GO:0019674
4  ENSG00000008130 IPR002504 GO:0046872
5  ENSG00000008130 IPR002504 GO:0016740
6  ENSG00000008130 IPR002504 GO:0005524
7  ENSG00000008130 IPR002504 GO:0005515
8  ENSG00000008130 IPR002504 GO:0003951
9  ENSG00000008130 IPR002504 GO:0000166
10 ENSG00000008130 IPR002504 GO:0016310
11 ENSG00000008130 IPR002504 GO:0008152
12 ENSG00000008130 IPR002504 GO:0006741
13 ENSG00000008130 IPR002504 GO:0016301
14 ENSG00000008130 IPR016064 GO:0005829
15 ENSG00000008130 IPR016064 GO:0046034
16 ENSG00000008130 IPR016064 GO:0019674
17 ENSG00000008130 IPR016064 GO:0046872
18 ENSG00000008130 IPR016064 GO:0016740
19 ENSG00000008130 IPR016064 GO:0005524
20 ENSG00000008130 IPR016064 GO:0005515
21 ENSG00000008130 IPR016064 GO:0003951
22 ENSG00000008130 IPR016064 GO:0000166
23 ENSG00000008130 IPR016064 GO:0016310
24 ENSG00000008130 IPR016064 GO:0008152
25 ENSG00000008130 IPR016064 GO:0006741
26 ENSG00000008130 IPR016064 GO:0016301
27 ENSG00000008130 IPR017437 GO:0005829
28 ENSG00000008130 IPR017437 GO:0046034
29 ENSG00000008130 IPR017437 GO:0019674
30 ENSG00000008130 IPR017437 GO:0046872
31 ENSG00000008130 IPR017437 GO:0016740
32 ENSG00000008130 IPR017437 GO:0005524
33 ENSG00000008130 IPR017437 GO:0005515
34 ENSG00000008130 IPR017437 GO:0003951
35 ENSG00000008130 IPR017437 GO:0000166
36 ENSG00000008130 IPR017437 GO:0016310
37 ENSG00000008130 IPR017437 GO:0008152
38 ENSG00000008130 IPR017437 GO:0006741
39 ENSG00000008130 IPR017437 GO:0016301
40 ENSG00000008130 IPR017438 GO:0005829
41 ENSG00000008130 IPR017438 GO:0046034
42 ENSG00000008130 IPR017438 GO:0019674
43 ENSG00000008130 IPR017438 GO:0046872
44 ENSG00000008130 IPR017438 GO:0016740
45 ENSG00000008130 IPR017438 GO:0005524
46 ENSG00000008130 IPR017438 GO:0005515
47 ENSG00000008130 IPR017438 GO:0003951
48 ENSG00000008130 IPR017438 GO:0000166
49 ENSG00000008130 IPR017438 GO:0016310
50 ENSG00000008130 IPR017438 GO:0008152
51 ENSG00000008130 IPR017438 GO:0006741
52 ENSG00000008130 IPR017438 GO:0016301
53 ENSG00000008130 

I hope this example demonstrates the advantage of the biomartr
package over the biomaRt package when constructing BioMart queries.

Please don't forget to cite my paper, so that I can keep
developing this package :)

Hajk-Georg Drost, Jerzy Paszkowski; Biomartr: genomic data retrieval with R. Bioinformatics 2017 btw821. doi: 10.1093/bioinformatics/btw821

Many thanks in advance and I hope I could help you :)

Best wishes
Hajk