## ----style, echo=FALSE, results='asis', message=FALSE--------------------
BiocStyle::markdown()
## ----01install_pkgs, eval=FALSE------------------------------------------
# install.packages("BiocManager")
# BiocManager::install("AnnotationHub")
## ----02load_ah-----------------------------------------------------------
library("EuPathDB")
library("AnnotationHub")
# create an AnnotationHub connection
ah <- AnnotationHub()
# search for all EuPathDB resources
meta <- query(ah, "EuPathDB")
length(meta)
head(meta)
# types of EuPathDB data available
table(meta$rdataclass)
# distribution of resources by specific databases
table(meta$dataprovider)
# list of organisms for which resources are available
length(unique(meta$species))
head(unique(meta$species))
## ----03query_major-------------------------------------------------------
res <- query(ah, c("OrgDb", "Leishmania major strain Friedlin"))
res
## ----04get_orgdb, eval=FALSE---------------------------------------------
# chosen_ah <- res[[1]]
# chosen_ah
## ----05query_major_columns, eval=FALSE-----------------------------------
# # list available fields to retrieve
# orgdb <- chosen_ah
# columns(orgdb)
#
# # create a vector containing all gene ids for the organism
# gids <- keys(orgdb, keytype="GID")
# head(gids)
#
# # retrieve the chromosome, description, and biotype for each gene
# dat <- select(orgdb, keys=gids, keytype="GID", columns=c("CHR", "TYPE", "GENEDESCRIPTION"))
#
# head(dat)
#
# table(dat$TYPE)
# table(dat$CHR)
#
# # create a gene / GO term mapping
# gene_go_mapping <- select(orgdb, keys=gids, keytype='GID',
# columns=c("GO_ID", "GO_TERM_NAME", "ONTOLOGY"))
# head(gene_go_mapping)
#
# # retrieve KEGG, etc. pathway annotations
# gene_pathway_mapping <- select(orgdb, keys=gids, keytype="GID",
# columns=c("PATHWAY", "PATHWAY_SOURCE"))
# table(gene_pathway_mapping$PATHWAY_SOURCE)
# head(gene_pathway_mapping)
## ----06query_granges-----------------------------------------------------
# query AnnotationHub
res <- query(ah, c("Leishmania major strain Friedlin", "GRanges", "EuPathDB"))
res
# retrieve a GRanges instance associated with the result record
gr <- res[[1]]
summary(gr)
head(gr)
## ----07extract_granges---------------------------------------------------
# chromosome names
seqnames(gr)
# strand information
strand(gr)
# feature widths
head(width(gr))
## ----08get_types---------------------------------------------------------
# list of location types in the resource
table(gr$type)
table(gr@strand)
## ----09chr4--------------------------------------------------------------
# get the first three ranges
gr[1:3]
# get all gene entries on chromosome 4
chr4_genes <- gr[gr$type == 'gene' & seqnames(gr) == 'LmjF.04']
summary(chr4_genes)
## Hey, checkit, there are 130 genes on chromosome 4.
## ----10session_info------------------------------------------------------
sessionInfo()
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