ensembldb 2.16.4
From Bioconductor release 3.5 on, EnsDb databases/packages created by the
ensembldb package contain also, for transcripts with a coding regions, mappings
between transcripts and proteins. Thus, in addition to the RNA/DNA-based
features also the following protein related information is available:
protein_id: the Ensembl protein ID. This is the primary ID for the proteins
defined in Ensembl and each (protein coding) Ensembl transcript has one
protein ID assigned to it.protein_sequence: the amino acid sequence of a protein.uniprot_id: the Uniprot ID for a protein. Note that not every Ensembl
protein_id has an Uniprot ID, and each protein_id might be mapped to several
uniprot_id. Also, the same Uniprot ID might be mapped to different protein_id.uniprot_db: the name of the Uniprot database in which the feature is
annotated. Can be either SPTREMBL or SWISSPROT.uniprot_mapping_type: the type of the mapping method that was used to assign
the Uniprot ID to the Ensembl protein ID.protein_domain_id: the ID of the protein domain according to the
source/analysis in/by which is was defined.protein_domain_source: the source of the protein domain information, one of
pfscan, scanprosite, superfamily, pfam, prints, smart, pirsf or tigrfam.interpro_accession: the Interpro accession ID of the protein domain (if
available).prot_dom_start: the start of the protein domain within the sequence of
the protein.prot_dom_start: the end position of the protein domain within the
sequence of the protein.Thus, for protein coding transcripts, these annotations can be fetched from the
database too, given that protein annotations are available. Note that only EnsDb
databases created through the Ensembl Perl API contain protein annotation, while
databases created using ensDbFromAH, ensDbFromGff, ensDbFromGRanges and
ensDbFromGtf don’t.
library(ensembldb)
library(EnsDb.Hsapiens.v86)
edb <- EnsDb.Hsapiens.v86
## Evaluate whether we have protein annotation available
hasProteinData(edb)## [1] TRUEIf protein annotation is available, the additional tables and columns are also
listed by the listTables and listColumns methods.
listTables(edb)## $gene
## [1] "gene_id" "gene_name" "gene_biotype" "gene_seq_start"
## [5] "gene_seq_end" "seq_name" "seq_strand" "seq_coord_system"
## [9] "symbol"
##
## $tx
## [1] "tx_id" "tx_biotype" "tx_seq_start" "tx_seq_end"
## [5] "tx_cds_seq_start" "tx_cds_seq_end" "gene_id" "tx_name"
##
## $tx2exon
## [1] "tx_id" "exon_id" "exon_idx"
##
## $exon
## [1] "exon_id" "exon_seq_start" "exon_seq_end"
##
## $chromosome
## [1] "seq_name" "seq_length" "is_circular"
##
## $protein
## [1] "tx_id" "protein_id" "protein_sequence"
##
## $uniprot
## [1] "protein_id" "uniprot_id" "uniprot_db"
## [4] "uniprot_mapping_type"
##
## $protein_domain
## [1] "protein_id" "protein_domain_id" "protein_domain_source"
## [4] "interpro_accession" "prot_dom_start" "prot_dom_end"
##
## $entrezgene
## [1] "gene_id" "entrezid"
##
## $metadata
## [1] "name" "value"In the following sections we show examples how to 1) fetch protein annotations as additional columns to gene/transcript annotations, 2) fetch protein annotation data and 3) map proteins to the genome.
Protein annotations for (protein coding) transcripts can be retrieved by simply
adding the desired annotation columns to the columns parameter of the e.g. genes
or transcripts methods.
## Get also protein information for ZBTB16 transcripts
txs <- transcripts(edb, filter = GeneNameFilter("ZBTB16"),
columns = c("protein_id", "uniprot_id", "tx_biotype"))
txs## GRanges object with 11 ranges and 5 metadata columns:
## seqnames ranges strand | protein_id
## <Rle> <IRanges> <Rle> | <character>
## ENST00000335953 11 114059593-114250676 + | ENSP00000338157
## ENST00000335953 11 114059593-114250676 + | ENSP00000338157
## ENST00000541602 11 114059725-114189764 + | <NA>
## ENST00000544220 11 114059737-114063646 + | ENSP00000437716
## ENST00000535700 11 114060257-114063744 + | ENSP00000443013
## ENST00000392996 11 114060507-114250652 + | ENSP00000376721
## ENST00000392996 11 114060507-114250652 + | ENSP00000376721
## ENST00000539918 11 114064412-114247344 + | ENSP00000445047
## ENST00000545851 11 114180766-114247296 + | <NA>
## ENST00000535379 11 114237207-114250557 + | <NA>
## ENST00000535509 11 114246790-114250476 + | <NA>
## uniprot_id tx_biotype tx_id
## <character> <character> <character>
## ENST00000335953 Q05516 protein_coding ENST00000335953
## ENST00000335953 A0A024R3C6 protein_coding ENST00000335953
## ENST00000541602 <NA> retained_intron ENST00000541602
## ENST00000544220 F5H6C3 protein_coding ENST00000544220
## ENST00000535700 F5H5Y7 protein_coding ENST00000535700
## ENST00000392996 Q05516 protein_coding ENST00000392996
## ENST00000392996 A0A024R3C6 protein_coding ENST00000392996
## ENST00000539918 H0YGW2 nonsense_mediated_de.. ENST00000539918
## ENST00000545851 <NA> processed_transcript ENST00000545851
## ENST00000535379 <NA> processed_transcript ENST00000535379
## ENST00000535509 <NA> retained_intron ENST00000535509
## gene_name
## <character>
## ENST00000335953 ZBTB16
## ENST00000335953 ZBTB16
## ENST00000541602 ZBTB16
## ENST00000544220 ZBTB16
## ENST00000535700 ZBTB16
## ENST00000392996 ZBTB16
## ENST00000392996 ZBTB16
## ENST00000539918 ZBTB16
## ENST00000545851 ZBTB16
## ENST00000535379 ZBTB16
## ENST00000535509 ZBTB16
## -------
## seqinfo: 1 sequence from GRCh38 genomeThe gene ZBTB16 has protein coding and non-coding transcripts, thus, we get the
protein ID for the coding- and NA for the non-coding transcripts. Note also that
we have a transcript targeted for nonsense mediated mRNA-decay with a protein ID
associated with it, but no Uniprot ID.
## Subset to transcripts with tx_biotype other than protein_coding.
txs[txs$tx_biotype != "protein_coding", c("uniprot_id", "tx_biotype",
"protein_id")]## GRanges object with 5 ranges and 3 metadata columns:
## seqnames ranges strand | uniprot_id
## <Rle> <IRanges> <Rle> | <character>
## ENST00000541602 11 114059725-114189764 + | <NA>
## ENST00000539918 11 114064412-114247344 + | H0YGW2
## ENST00000545851 11 114180766-114247296 + | <NA>
## ENST00000535379 11 114237207-114250557 + | <NA>
## ENST00000535509 11 114246790-114250476 + | <NA>
## tx_biotype protein_id
## <character> <character>
## ENST00000541602 retained_intron <NA>
## ENST00000539918 nonsense_mediated_de.. ENSP00000445047
## ENST00000545851 processed_transcript <NA>
## ENST00000535379 processed_transcript <NA>
## ENST00000535509 retained_intron <NA>
## -------
## seqinfo: 1 sequence from GRCh38 genomeWhile the mapping from a protein coding transcript to a Ensembl protein ID
(column protein_id) is 1:1, the mapping between protein_id and uniprot_id can be
n:m, i.e. each Ensembl protein ID can be mapped to 1 or more Uniprot IDs and
each Uniprot ID can be mapped to more than one protein_id (and hence
tx_id). This should be kept in mind if querying transcripts from the database
fetching Uniprot related additional columns or even protein ID features, as in
such cases a redundant list of transcripts is returned.
## List the protein IDs and uniprot IDs for the coding transcripts
mcols(txs[txs$tx_biotype == "protein_coding",
c("tx_id", "protein_id", "uniprot_id")])## DataFrame with 6 rows and 3 columns
## tx_id protein_id uniprot_id
## <character> <character> <character>
## ENST00000335953 ENST00000335953 ENSP00000338157 Q05516
## ENST00000335953 ENST00000335953 ENSP00000338157 A0A024R3C6
## ENST00000544220 ENST00000544220 ENSP00000437716 F5H6C3
## ENST00000535700 ENST00000535700 ENSP00000443013 F5H5Y7
## ENST00000392996 ENST00000392996 ENSP00000376721 Q05516
## ENST00000392996 ENST00000392996 ENSP00000376721 A0A024R3C6Some of the n:m mappings for Uniprot IDs can be resolved by restricting either
to entries from one Uniprot database (SPTREMBL or SWISSPROT) or to mappings of a
certain type of mapping method. The corresponding filters are the
UniprotDbFilter and the UniprotMappingTypeFilter (using the uniprot_db and
uniprot_mapping_type columns of the uniprot database table). In the example
below we restrict the result to Uniprot IDs with the mapping type DIRECT.
## List all uniprot mapping types in the database.
listUniprotMappingTypes(edb)## [1] "DIRECT" "SEQUENCE_MATCH"## Get all protein_coding transcripts of ZBTB16 along with their protein_id
## and Uniprot IDs, restricting to protein_id to uniprot_id mappings based
## on "DIRECT" mapping methods.
txs <- transcripts(edb, filter = list(GeneNameFilter("ZBTB16"),
UniprotMappingTypeFilter("DIRECT")),
columns = c("protein_id", "uniprot_id", "uniprot_db"))
mcols(txs)## DataFrame with 5 rows and 6 columns
## protein_id uniprot_id uniprot_db tx_id
## <character> <character> <character> <character>
## ENST00000335953 ENSP00000338157 Q05516 SWISSPROT ENST00000335953
## ENST00000544220 ENSP00000437716 F5H6C3 SPTREMBL ENST00000544220
## ENST00000535700 ENSP00000443013 F5H5Y7 SPTREMBL ENST00000535700
## ENST00000392996 ENSP00000376721 Q05516 SWISSPROT ENST00000392996
## ENST00000539918 ENSP00000445047 H0YGW2 SPTREMBL ENST00000539918
## gene_name uniprot_mapping_type
## <character> <character>
## ENST00000335953 ZBTB16 DIRECT
## ENST00000544220 ZBTB16 DIRECT
## ENST00000535700 ZBTB16 DIRECT
## ENST00000392996 ZBTB16 DIRECT
## ENST00000539918 ZBTB16 DIRECTFor this example the use of the UniprotMappingTypeFilter resolved the multiple
mapping of Uniprot IDs to Ensembl protein IDs, but the Uniprot ID Q05516 is
still assigned to the two Ensembl protein IDs ENSP00000338157 and
ENSP00000376721.
All protein annotations can also be added as metadata columns to the
results of the genes, exons, exonsBy, transcriptsBy, cdsBy, fiveUTRsByTranscript
and threeUTRsByTranscript methods by specifying the desired column names with
the columns parameter. For non coding transcripts NA will be reported in the
protein annotation columns.
In addition to retrieve protein annotations from the database, we can also use protein data to filter the results. In the example below we fetch for example all genes from the database that have a certain protein domain in the protein encoded by any of its transcripts.
## Get all genes encoded on chromosome 11 which protein contains
## a certain protein domain.
gns <- genes(edb, filter = ~ prot_dom_id == "PS50097" & seq_name == "11")
length(gns)## [1] 9sort(gns$gene_name)## [1] "ABTB2" "BTBD18" "KBTBD3" "KBTBD4" "KCTD21" "KLHL35" "ZBTB16" "ZBTB3"
## [9] "ZBTB44"So, in total we got 152 genes with that protein domain. In addition to the
ProtDomIdFilter, also the ProteinidFilter and the UniprotidFilter can be used to
query the database for entries matching conditions on their protein ID or
Uniprot ID.
AnnotationDbi package to query protein annotationThe select, keys and mapIds methods from the AnnotationDbi package can also be
used to query EnsDb objects for protein annotations. Supported columns and
key types are returned by the columns and keytypes methods.
## Show all columns that are provided by the database
columns(edb)## [1] "ENTREZID" "EXONID" "EXONIDX"
## [4] "EXONSEQEND" "EXONSEQSTART" "GENEBIOTYPE"
## [7] "GENEID" "GENENAME" "GENESEQEND"
## [10] "GENESEQSTART" "INTERPROACCESSION" "ISCIRCULAR"
## [13] "PROTDOMEND" "PROTDOMSTART" "PROTEINDOMAINID"
## [16] "PROTEINDOMAINSOURCE" "PROTEINID" "PROTEINSEQUENCE"
## [19] "SEQCOORDSYSTEM" "SEQLENGTH" "SEQNAME"
## [22] "SEQSTRAND" "SYMBOL" "TXBIOTYPE"
## [25] "TXCDSSEQEND" "TXCDSSEQSTART" "TXID"
## [28] "TXNAME" "TXSEQEND" "TXSEQSTART"
## [31] "UNIPROTDB" "UNIPROTID" "UNIPROTMAPPINGTYPE"## Show all key types/filters that are supported
keytypes(edb)## [1] "ENTREZID" "EXONID" "GENEBIOTYPE"
## [4] "GENEID" "GENENAME" "PROTDOMID"
## [7] "PROTEINDOMAINID" "PROTEINDOMAINSOURCE" "PROTEINID"
## [10] "SEQNAME" "SEQSTRAND" "SYMBOL"
## [13] "TXBIOTYPE" "TXID" "TXNAME"
## [16] "UNIPROTID"Below we fetch all Uniprot IDs annotated to the gene ZBTB16.
select(edb, keys = "ZBTB16", keytype = "GENENAME",
columns = "UNIPROTID")## GENENAME UNIPROTID
## 1 ZBTB16 Q05516
## 2 ZBTB16 A0A024R3C6
## 3 ZBTB16 <NA>
## 4 ZBTB16 F5H6C3
## 5 ZBTB16 F5H5Y7
## 6 ZBTB16 H0YGW2This returns us all Uniprot IDs of all proteins encoded by the gene’s
transcripts. One of the transcripts from ZBTB16, while having a CDS and being
annotated to a protein, does not have an Uniprot ID assigned (thus NA is
returned by the above call). As we see below, this transcript is targeted for
non sense mediated mRNA decay.
## Call select, this time providing a GeneNameFilter.
select(edb, keys = GeneNameFilter("ZBTB16"),
columns = c("TXBIOTYPE", "UNIPROTID", "PROTEINID"))## TXBIOTYPE UNIPROTID PROTEINID GENENAME
## 1 protein_coding Q05516 ENSP00000338157 ZBTB16
## 2 protein_coding A0A024R3C6 ENSP00000338157 ZBTB16
## 3 retained_intron <NA> <NA> ZBTB16
## 4 protein_coding F5H6C3 ENSP00000437716 ZBTB16
## 5 protein_coding F5H5Y7 ENSP00000443013 ZBTB16
## 6 protein_coding Q05516 ENSP00000376721 ZBTB16
## 7 protein_coding A0A024R3C6 ENSP00000376721 ZBTB16
## 8 nonsense_mediated_decay H0YGW2 ENSP00000445047 ZBTB16
## 9 processed_transcript <NA> <NA> ZBTB16Note also that we passed this time a GeneMameFilter with the keys parameter.
Proteins can be fetched using the dedicated proteins method that returns, unlike
DNA/RNA-based methods like genes or transcripts, not a GRanges object by
default, but a DataFrame object. Alternatively, results can be returned as a
data.frame or as an AAStringSet object from the Biobase package. Note that this
might change in future releases if a more appropriate object to represent
protein annotations becomes available.
In the code chunk below we fetch all protein annotations for the gene ZBTB16.
## Get all proteins and return them as an AAStringSet
prts <- proteins(edb, filter = GeneNameFilter("ZBTB16"),
return.type = "AAStringSet")
prts## AAStringSet object of length 5:
## width seq names
## [1] 673 MDLTKMGMIQLQNPSHPTGLLCK...GHKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## [2] 115 MDLTKMGMIQLQNPSHPTGLLCK...QAKAEDLDDLLYAAEILEIEYLE ENSP00000437716
## [3] 148 MDLTKMGMIQLQNPSHPTGLLCK...QASDDNDTEATMADGGAEEEEDR ENSP00000443013
## [4] 673 MDLTKMGMIQLQNPSHPTGLLCK...GHKPEEIPPDWRIEKTYLYLCYV ENSP00000376721
## [5] 55 XGGLLPQGFIQRELFSKLGELAV...GEQCSVCGVELPDNEAVEQHRVF ENSP00000445047Besides the amino acid sequence, the prts contains also additional annotations
that can be accessed with the mcols method (metadata columns). All additional
columns provided with the parameter columns are also added to the mcols
DataFrame.
mcols(prts)## DataFrame with 5 rows and 3 columns
## tx_id protein_id gene_name
## <character> <character> <character>
## ENSP00000338157 ENST00000335953 ENSP00000338157 ZBTB16
## ENSP00000437716 ENST00000544220 ENSP00000437716 ZBTB16
## ENSP00000443013 ENST00000535700 ENSP00000443013 ZBTB16
## ENSP00000376721 ENST00000392996 ENSP00000376721 ZBTB16
## ENSP00000445047 ENST00000539918 ENSP00000445047 ZBTB16Note that the proteins method will retrieve only gene/transcript annotations of
transcripts encoding a protein. Thus annotations for the non-coding transcripts
of the gene ZBTB16, that were returned by calls to genes or transcripts in the
previous section are not fetched.
Querying in addition Uniprot identifiers or protein domain data will result at present in a redundant list of proteins as shown in the code block below.
## Get also protein domain annotations in addition to the protein annotations.
pd <- proteins(edb, filter = GeneNameFilter("ZBTB16"),
columns = c("tx_id", listColumns(edb, "protein_domain")),
return.type = "AAStringSet")
pd## AAStringSet object of length 81:
## width seq names
## [1] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## [2] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## [3] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## [4] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## [5] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000338157
## ... ... ...
## [77] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000376721
## [78] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000376721
## [79] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000376721
## [80] 673 MDLTKMGMIQLQNPSHPTGLLCK...HKPEEIPPDWRIEKTYLYLCYV ENSP00000376721
## [81] 55 XGGLLPQGFIQRELFSKLGELAV...EQCSVCGVELPDNEAVEQHRVF ENSP00000445047The result contains one row/element for each protein domain in each of the
proteins. The number of protein domains per protein and the mcols are shown
below.
## The number of protein domains per protein:
table(names(pd))##
## ENSP00000338157 ENSP00000376721 ENSP00000437716 ENSP00000443013 ENSP00000445047
## 36 36 4 4 1## The mcols
mcols(pd)## DataFrame with 81 rows and 8 columns
## tx_id protein_id protein_domain_id
## <character> <character> <character>
## ENSP00000338157 ENST00000335953 ENSP00000338157 PS50157
## ENSP00000338157 ENST00000335953 ENSP00000338157 PS50157
## ENSP00000338157 ENST00000335953 ENSP00000338157 PS50157
## ENSP00000338157 ENST00000335953 ENSP00000338157 PS50157
## ENSP00000338157 ENST00000335953 ENSP00000338157 PS50157
## ... ... ... ...
## ENSP00000376721 ENST00000392996 ENSP00000376721 SM00355
## ENSP00000376721 ENST00000392996 ENSP00000376721 SM00355
## ENSP00000376721 ENST00000392996 ENSP00000376721 SM00355
## ENSP00000376721 ENST00000392996 ENSP00000376721 SM00355
## ENSP00000445047 ENST00000539918 ENSP00000445047 NA
## protein_domain_source interpro_accession prot_dom_start
## <character> <character> <integer>
## ENSP00000338157 pfscan IPR007087 602
## ENSP00000338157 pfscan IPR007087 490
## ENSP00000338157 pfscan IPR007087 630
## ENSP00000338157 pfscan IPR007087 432
## ENSP00000338157 pfscan IPR007087 546
## ... ... ... ...
## ENSP00000376721 smart IPR015880 546
## ENSP00000376721 smart IPR015880 574
## ENSP00000376721 smart IPR015880 602
## ENSP00000376721 smart IPR015880 630
## ENSP00000445047 NA NA NA
## prot_dom_end gene_name
## <integer> <character>
## ENSP00000338157 629 ZBTB16
## ENSP00000338157 517 ZBTB16
## ENSP00000338157 657 ZBTB16
## ENSP00000338157 459 ZBTB16
## ENSP00000338157 573 ZBTB16
## ... ... ...
## ENSP00000376721 568 ZBTB16
## ENSP00000376721 596 ZBTB16
## ENSP00000376721 624 ZBTB16
## ENSP00000376721 652 ZBTB16
## ENSP00000445047 NA ZBTB16As we can see each protein can have several protein domains with the start and
end coordinates within the amino acid sequence being reported in columns
prot_dom_start and prot_dom_end. Also, not all Ensembl protein IDs, like
protein_id ENSP00000445047 are mapped to an Uniprot ID or have protein domains.
The coordinate-mapping.Rmd vignette provides a detailed description of all functions that allow to map between genomic, transcript and protein coordinates.
sessionInfo() ## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.13-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] grid stats4 parallel stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] AnnotationHub_3.0.1
## [2] BiocFileCache_2.0.0
## [3] dbplyr_2.1.1
## [4] magrittr_2.0.1
## [5] BSgenome.Hsapiens.NCBI.GRCh38_1.3.1000
## [6] BSgenome_1.60.0
## [7] rtracklayer_1.52.0
## [8] Biostrings_2.60.2
## [9] XVector_0.32.0
## [10] Gviz_1.36.2
## [11] EnsDb.Hsapiens.v86_2.99.0
## [12] ensembldb_2.16.4
## [13] AnnotationFilter_1.16.0
## [14] GenomicFeatures_1.44.0
## [15] AnnotationDbi_1.54.1
## [16] Biobase_2.52.0
## [17] GenomicRanges_1.44.0
## [18] GenomeInfoDb_1.28.1
## [19] IRanges_2.26.0
## [20] S4Vectors_0.30.0
## [21] BiocGenerics_0.38.0
## [22] BiocStyle_2.20.2
##
## loaded via a namespace (and not attached):
## [1] colorspace_2.0-2 rjson_0.2.20
## [3] ellipsis_0.3.2 biovizBase_1.40.0
## [5] htmlTable_2.2.1 base64enc_0.1-3
## [7] dichromat_2.0-0 rstudioapi_0.13
## [9] bit64_4.0.5 interactiveDisplayBase_1.30.0
## [11] fansi_0.5.0 xml2_1.3.2
## [13] splines_4.1.0 cachem_1.0.5
## [15] knitr_1.33 Formula_1.2-4
## [17] jsonlite_1.7.2 Rsamtools_2.8.0
## [19] cluster_2.1.2 png_0.1-7
## [21] shiny_1.6.0 BiocManager_1.30.16
## [23] compiler_4.1.0 httr_1.4.2
## [25] backports_1.2.1 assertthat_0.2.1
## [27] Matrix_1.3-4 fastmap_1.1.0
## [29] lazyeval_0.2.2 later_1.2.0
## [31] htmltools_0.5.1.1 prettyunits_1.1.1
## [33] tools_4.1.0 gtable_0.3.0
## [35] glue_1.4.2 GenomeInfoDbData_1.2.6
## [37] dplyr_1.0.7 rappdirs_0.3.3
## [39] Rcpp_1.0.7 jquerylib_0.1.4
## [41] vctrs_0.3.8 xfun_0.24
## [43] stringr_1.4.0 mime_0.11
## [45] lifecycle_1.0.0 restfulr_0.0.13
## [47] XML_3.99-0.6 zlibbioc_1.38.0
## [49] scales_1.1.1 VariantAnnotation_1.38.0
## [51] promises_1.2.0.1 hms_1.1.0
## [53] MatrixGenerics_1.4.1 ProtGenerics_1.24.0
## [55] SummarizedExperiment_1.22.0 RColorBrewer_1.1-2
## [57] yaml_2.2.1 curl_4.3.2
## [59] memoise_2.0.0 gridExtra_2.3
## [61] ggplot2_3.3.5 sass_0.4.0
## [63] biomaRt_2.48.2 rpart_4.1-15
## [65] latticeExtra_0.6-29 stringi_1.7.3
## [67] RSQLite_2.2.7 BiocVersion_3.13.1
## [69] highr_0.9 BiocIO_1.2.0
## [71] checkmate_2.0.0 filelock_1.0.2
## [73] BiocParallel_1.26.1 rlang_0.4.11
## [75] pkgconfig_2.0.3 matrixStats_0.60.0
## [77] bitops_1.0-7 evaluate_0.14
## [79] lattice_0.20-44 purrr_0.3.4
## [81] GenomicAlignments_1.28.0 htmlwidgets_1.5.3
## [83] bit_4.0.4 tidyselect_1.1.1
## [85] bookdown_0.22 R6_2.5.0
## [87] magick_2.7.2 generics_0.1.0
## [89] Hmisc_4.5-0 DelayedArray_0.18.0
## [91] DBI_1.1.1 withr_2.4.2
## [93] pillar_1.6.2 foreign_0.8-81
## [95] survival_3.2-11 KEGGREST_1.32.0
## [97] RCurl_1.98-1.3 nnet_7.3-16
## [99] tibble_3.1.3 crayon_1.4.1
## [101] utf8_1.2.2 rmarkdown_2.9
## [103] jpeg_0.1-9 progress_1.2.2
## [105] data.table_1.14.0 blob_1.2.2
## [107] digest_0.6.27 xtable_1.8-4
## [109] httpuv_1.6.1 munsell_0.5.0
## [111] bslib_0.2.5.1