1 BioMartデータベースのリスト listMarts

• ホスト名http://ensemblgenomes.org/info/data_access で探す。
• listMarts(host = "www.ensembl.org")利用可能なBioMartデータベースを参照
• 繋がらない場合はミラーを選択する。asia.ensembl.orgとか
• bacteriaはbiomartを使えない。

# 利用可能なBioMartデータベースを'www.ensembl.org'から探す
biomaRt::listMarts(host = "www.ensembl.org", verbose = F)

##                biomart               version
## 1 ENSEMBL_MART_ENSEMBL      Ensembl Genes 95
## 2   ENSEMBL_MART_MOUSE      Mouse strains 95
## 3     ENSEMBL_MART_SNP  Ensembl Variation 95
## 4 ENSEMBL_MART_FUNCGEN Ensembl Regulation 95

# ホスト名は以下の中から選択
hosts <- c("www.ensembl.org", "plants.ensembl.org", "fungi.ensembl.org", 
           "protists.ensembl.org", "metazoa.ensembl.org")

# 利用可能なBioMartデータベースを探す
marts <- Reduce(rbind, lapply(seq_along(hosts), function(i){
  biomaRt::listMarts(host = hosts[i]) %>%
    mutate(host_name= rep(hosts[i], nrow(.)))
  }))

knitr::kable(marts, format = "pandoc", align = "l", caption="listMarts")

2 BioMartデータベース内で使用可能なデータセットを参照 listDatasets

• 最初にuseMartを使用してBioMartデータベースを選択してから、選択したBioMartでlistDatasetsを使用。

marts <- c("ENSEMBL_MART_ENSEMBL", "plants_mart", "fungi_mart", "protists_mart", "metazoa_mart")
hosts <- c("www.ensembl.org", "plants.ensembl.org", "fungi.ensembl.org",
           "protists.ensembl.org", "metazoa.ensembl.org" )

l_dsets <- mapply(function(x,y){
  listDatasets(useMart(biomart = x, host = y), verbose = F) 
  }, x = marts, y = hosts, SIMPLIFY = F
  )

dsets <- lapply(seq_along(l_dsets), function(i){
  l_dsets[[i]] %>% 
    mutate(biomart=rep(marts[i], nrow(.)), host_name=rep(hosts[i], nrow(.))) %>%
    dplyr::select(c(4,5,1:3))
  }) %>%
  {Reduce(rbind, .)}

knitr::kable(head(dsets), format = "pandoc", align = "l", caption="DataSet")

# descriptionから目的の生物種を検索
# grep("chinese hamster",dsets$description, ignore.case = T)
args <- unlist(dsets[18, 1:3])

# データセットに接続
cg_mart <- useMart(biomart = args[1], host = args[2], dataset = args[3])

3 データベースからデータを取得する

# この中から欲しいattribute選ぶ。たくさんある。   
attr_cg_mart <- listAttributes(cg_mart)
knitr::kable(head(attr_cg_mart), format = "pandoc", align = "l", caption="Attributes of mart")

# selected attributes　
atr_1 <- c("chromosome_name", "ensembl_transcript_id", "ensembl_peptide_id", 
            "external_gene_name", "description")
atr_2 = c("chromosome_name","start_position", "end_position", 
           "external_gene_name", "ensembl_transcript_id", "strand", 
           "cds_start", "cds_end", "description")

# getBM
dat1_cg_mart <- getBM(attributes = atr_1, mart = cg_mart)


# getBM with filters : protein codingのもの以外をfilterする(全部は時間がかかるので一部試す).
dat1_cg_mart %>% 
  filter(chromosome_name == "JH000064.1", ensembl_peptide_id !="") %>%
  pull(ensembl_transcript_id) -> enst
  
dat2_cg_mart <- getBM(attributes = atr_2, filters = "ensembl_transcript_id", 
                      values = enst, mart = cg_mart)

# 一部表示
knitr::kable(head(dat1_cg_mart), format="pandoc", align="l", caption="Attributes of mart(id retrieve)")

knitr::kable(head(dat2_cg_mart), format="pandoc", align="l", caption="Attributes of mart(bed like)")

4 配列を取得 getSequence

• “ENSEMBL_MART_ENSEMBL”でしか使えないらしい
• seqTypeは以下の中から選択’cdna’, ‘peptide’, ‘3utr’, ‘5utr’, ‘gene_exon’, ‘transcript_exon_intron’, ‘gene_exon_intron’, ‘coding’, ‘coding_transcript_flank’, ‘transcript_flank’, ‘gene_flank’
• idの並びが変わっていることに注意
• typeはlistFiltersでつかわれるフィルターのタイプで指定する。

# startとendを指定してその中にあるseqTypeのものを取得する
seq_1 <- getSequence(chromosome = "JH000064.1", start = 2214310, end = 2216976, 
                     type="ensembl_transcript_id", seqType="cdna", mart=cg_mart)

# idを指定して
flt <- c("ENSCGRT00000009189","ENSCGRT00000009188","ENSCGRT00000009190")
seq_2　<- getSequence(id = flt, type = "ensembl_transcript_id", seqType="coding", mart=cg_mart)
seq_3　<- getSequence(id = flt, type = "ensembl_transcript_id", seqType="peptide", mart=cg_mart)

# pick the part of seq
suppressPackageStartupMessages(library(dplyr))
seq_1_tab <- seq_1 %>% mutate(cdna = substr(seq_1$cdna, 1, 50))
seq_2_tab <- seq_2 %>% mutate(coding = substr(seq_2$coding, 1, 50))
seq_3_tab <- seq_3 %>% mutate(peptide = substr(seq_3$peptide, 1, 50))

knitr::kable(seq_1_tab, format = "markdown", align = "l", caption="cdna")

knitr::kable(seq_2_tab, format = "markdown", align = "l", caption="coding")

knitr::kable(seq_3_tab, format = "markdown", align = "l", caption="peptide")

5 環境

sessionInfo()

## R version 3.5.1 (2018-07-02)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Sierra 10.12.6
## 
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] ja_JP.UTF-8/ja_JP.UTF-8/ja_JP.UTF-8/C/ja_JP.UTF-8/ja_JP.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] bindrcpp_0.2.2 dplyr_0.7.8    biomaRt_2.36.1
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.0           highr_0.7            pillar_1.3.1        
##  [4] compiler_3.5.1       bindr_0.1.1          prettyunits_1.0.2   
##  [7] bitops_1.0-6         tools_3.5.1          progress_1.2.0      
## [10] digest_0.6.18        bit_1.1-14           tibble_2.0.0        
## [13] RSQLite_2.1.1        evaluate_0.12        memoise_1.1.0       
## [16] pkgconfig_2.0.2      rlang_0.3.1          DBI_1.0.0           
## [19] curl_3.2             yaml_2.2.0           parallel_3.5.1      
## [22] stringr_1.3.1        httr_1.3.1           knitr_1.20          
## [25] S4Vectors_0.18.3     IRanges_2.14.12      hms_0.4.2           
## [28] tidyselect_0.2.5     stats4_3.5.1         rprojroot_1.3-2     
## [31] bit64_0.9-7          glue_1.3.0           Biobase_2.40.0      
## [34] R6_2.3.0             AnnotationDbi_1.42.1 XML_3.98-1.16       
## [37] rmarkdown_1.10       purrr_0.2.5          blob_1.1.1          
## [40] magrittr_1.5         backports_1.1.2      htmltools_0.3.6     
## [43] BiocGenerics_0.26.0  assertthat_0.2.0     stringi_1.2.4       
## [46] RCurl_1.95-4.11      crayon_1.3.4