1 S. cerevisiae annotation data

There are a few methods of importing annotation data into R. I will attempt some of them in preparation for loading them into the S.cerevisiae RNASeq data.

2 AnnotationHub: loading OrgDb

AnnotationHub is a newer service and has promise to be an excellent top-level resource for gathering annotation data.

tmp <- sm(library(AnnotationHub))
ah = sm(AnnotationHub())
orgdbs <- sm(query(ah, "OrgDb"))
sc_orgdb <- sm(query(ah, c("OrgDB", "Saccharomyces"))) ##   AH49589 | org.Sc.sgd.db.sqlite
sc_orgdb <- ah[["AH49589"]]
## loading from cache '/home/trey//.AnnotationHub/56319'
## Loading required package: AnnotationDbi
## Loading required package: stats4
## Loading required package: Biobase
## Welcome to Bioconductor
## 
##     Vignettes contain introductory material; view with 'browseVignettes()'. To
##     cite Bioconductor, see 'citation("Biobase")', and for packages
##     'citation("pkgname")'.
## 
## Attaching package: 'Biobase'
## The following object is masked from 'package:AnnotationHub':
## 
##     cache
## Loading required package: IRanges
## Loading required package: S4Vectors
## 
## Attaching package: 'S4Vectors'
## The following objects are masked from 'package:base':
## 
##     colMeans, colSums, expand.grid, rowMeans, rowSums
sc_orgdb
## OrgDb object:
## | DBSCHEMAVERSION: 2.1
## | Db type: OrgDb
## | Supporting package: AnnotationDbi
## | DBSCHEMA: YEAST_DB
## | ORGANISM: Saccharomyces cerevisiae
## | SPECIES: Yeast
## | YGSOURCENAME: Yeast Genome
## | YGSOURCEURL: http://downloads.yeastgenome.org/
## | YGSOURCEDATE: 08-Aug-2015
## | CENTRALID: ORF
## | TAXID: 559292
## | KEGGSOURCENAME: KEGG GENOME
## | KEGGSOURCEURL: ftp://ftp.genome.jp/pub/kegg/genomes
## | KEGGSOURCEDATE: 2011-Mar15
## | GOSOURCENAME: Gene Ontology
## | GOSOURCEURL: ftp://ftp.geneontology.org/pub/go/godatabase/archive/latest-lite/
## | GOSOURCEDATE: 20150808
## | EGSOURCEDATE: 2015-Aug11
## | EGSOURCENAME: Entrez Gene
## | EGSOURCEURL: ftp://ftp.ncbi.nlm.nih.gov/gene/DATA
## | ENSOURCEDATE: 2015-Jul16
## | ENSOURCENAME: Ensembl
## | ENSOURCEURL: ftp://ftp.ensembl.org/pub/current_fasta
## | UPSOURCENAME: Uniprot
## | UPSOURCEURL: http://www.UniProt.org/
## | UPSOURCEDATE: Thu Aug 20 15:54:12 2015
## 
## Please see: help('select') for usage information
## Holy crap it worked!
sc_annotv1 <- load_orgdb_annotations(sc_orgdb,
                                     fields=c("alias", "description", "entrezid", "genename", "sgd"))
## Extracted all gene ids.
## 'select()' returned 1:many mapping between keys and columns
summary(sc_annotv1)
##             Length Class      Mode
## genes       6      data.frame list
## transcripts 0      -none-     NULL
sc_annotv1 <- sc_annotv1[["genes"]]
head(sc_annotv1)
##           ensembl              alias
## YGL261C   YGL261C  seripauperin PAU8
## YGL261C.1 YGL261C  seripauperin PAU9
## YGL261C.2 YGL261C seripauperin PAU11
## YAL068C   YAL068C  seripauperin PAU8
## YAL068C.1 YAL068C  seripauperin PAU9
## YAL068C.2 YAL068C seripauperin PAU11
##                                                                                                                                                                                  description
## YGL261C                                                                      Protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions
## YGL261C.1                                                                    Protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions
## YGL261C.2 Putative protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions; mRNA expression appears to be regulated by SUT1 and UPC2
## YAL068C                                                                      Protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions
## YAL068C.1                                                                    Protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions
## YAL068C.2 Putative protein of unknown function; member of the seripauperin multigene family encoded mainly in subtelomeric regions; mRNA expression appears to be regulated by SUT1 and UPC2
##           entrezid genename        sgd
## YGL261C     851229     PAU8 S000002142
## YGL261C.1   852163     PAU9 S000007592
## YGL261C.2   852630    PAU11 S000003230
## YAL068C     851229     PAU8 S000002142
## YAL068C.1   852163     PAU9 S000007592
## YAL068C.2   852630    PAU11 S000003230
require.auto("TxDb.Scerevisiae.UCSC.sacCer3.sgdGene")
## [1] 0
tmp <- sm(library(TxDb.Scerevisiae.UCSC.sacCer3.sgdGene))
sc_txdb <- TxDb.Scerevisiae.UCSC.sacCer3.sgdGene

3 Loading a genome

There is a non-zero chance we will want to use the actual genome sequence along with these annotations. The BSGenome packages provide that functionality.

tt <- sm(require.auto("BSgenome.Scerevisiae.UCSC.sacCer3"))

4 Loading a genome

There is a non-zero chance we will want to use the actual genome sequence along with these annotations. The BSGenome packages provide that functionality.

tt <- sm(require.auto("BSgenome.Scerevisiae.UCSC.sacCer3"))

5 Loading from biomart

A completely separate and competing annotation source is biomart.

sc_annotv2 <- sm(get_biomart_annotations("scerevisiae"))
head(sc_annotv2)
##           transcriptID   geneID
## X15S_rRNA     15S_rRNA 15S_rRNA
## X21S_rRNA     21S_rRNA 21S_rRNA
## HRA1              HRA1     HRA1
## ICR1              ICR1     ICR1
## LSR1              LSR1     LSR1
## NME1              NME1     NME1
##                                                                                                                                                                                                                                                                                    Description
## X15S_rRNA                                                                                                            Ribosomal RNA of the small mitochondrial ribosomal subunit; MSU1 allele suppresses ochre stop mutations in mitochondrial protein-coding genes [Source:SGD;Acc:S000007287]
## X21S_rRNA                                                                                                                                                                                       Mitochondrial 21S rRNA; intron encodes the I-SceI DNA endonuclease [Source:SGD;Acc:S000007288]
## HRA1                                                                                                         Non-protein-coding RNA; substrate of RNase P, possibly involved in rRNA processing, specifically maturation of 20S precursor into the mature 18S rRNA [Source:SGD;Acc:S000119380]
## ICR1      Long intergenic regulatory ncRNA; has a key role in regulating transcription of the nearby protein-coding ORF FLO11; initiated far upstream from FLO11 and transcribed across much of the large promoter of FLO11, repressing FLO11 transcription in cis [Source:SGD;Acc:S000132612]
## LSR1           U2 spliceosomal RNA (U2 snRNA), component of the spliceosome; pairs with the branchpoint sequence; functionally equivalent to mammalian U2 snRNA; stress-induced pseudouridylations at positions 56 and 93 may contribute to regulation of splicing [Source:SGD;Acc:S000006478]
## NME1                                                    RNA component of RNase MRP; RNase MRP cleaves pre-rRNA and has a role in cell cycle-regulated degradation of daughter cell-specific mRNAs; human ortholog is implicated in cartilage-hair hypoplasia (CHH) [Source:SGD;Acc:S000007436]
##             Type length chromosome strand  start    end
## X15S_rRNA   rRNA     NA       Mito      1   6546   8194
## X21S_rRNA   rRNA     NA       Mito      1  58009  62447
## HRA1       ncRNA     NA          I      1  99305  99868
## ICR1       ncRNA     NA         IX     -1 393884 397082
## LSR1       snRNA     NA         II     -1 680688 681862
## NME1      snoRNA     NA        XIV      1 585587 585926
sc_ontology <- sm(get_biomart_ontologies("scerevisiae"))

6 Read a gff file

In contrast, it is possible to load most annotations of interest directly from the gff files used in the alignments.

## The old way of getting genome/annotation data
sc_gff <- "reference/scerevisiae.gff.gz"
sc_gff_annotations <- gff2df(sc_gff, type="gene")
## Trying attempt: rtracklayer::import.gff3(gff, sequenceRegionsAsSeqinfo=TRUE)
## Trying attempt: rtracklayer::import.gff3(gff, sequenceRegionsAsSeqinfo=FALSE)
## Trying attempt: rtracklayer::import.gff2(gff, sequenceRegionsAsSeqinfo=TRUE)
## Had a successful gff import with rtracklayer::import.gff2(gff, sequenceRegionsAsSeqinfo=TRUE)
## Returning a df with 18 columns and 7050 rows.
rownames(sc_gff_annotations) <- make.names(sc_gff_annotations$transcript_name, unique=TRUE)
head(sc_gff_annotations)
##           seqnames start   end width strand         source type score phase exon_number
## YAL069W          I   335   646   312      + protein_coding gene    NA     0           1
## YAL068W.A        I   538   789   252      + protein_coding gene    NA     0           1
## PAU8             I  1810  2169   360      - protein_coding gene    NA     0           1
## YAL067W.A        I  2480  2704   225      + protein_coding gene    NA     0           1
## SEO1             I  7238  9016  1779      - protein_coding gene    NA     0           1
## YAL066W          I 10091 10396   306      + protein_coding gene    NA     0           1
##             gene_id        ID  p_id protein_id transcript_id transcript_name  tss_id
## YAL069W     YAL069W   YAL069W P3633    YAL069W       YAL069W         YAL069W TSS1128
## YAL068W.A YAL068W-A YAL068W-A P5377  YAL068W-A     YAL068W-A       YAL068W-A TSS5439
## PAU8        YAL068C      PAU8 P6023    YAL068C       YAL068C            PAU8  TSS249
## YAL067W.A YAL067W-A YAL067W-A P4547  YAL067W-A     YAL067W-A       YAL067W-A TSS1248
## SEO1        YAL067C      SEO1 P5747    YAL067C       YAL067C            SEO1 TSS5464
## YAL066W     YAL066W   YAL066W P1766    YAL066W       YAL066W         YAL066W TSS2674
##           seqedit
## YAL069W      <NA>
## YAL068W.A    <NA>
## PAU8         <NA>
## YAL067W.A    <NA>
## SEO1         <NA>
## YAL066W      <NA>

7 Putting the pieces together

In the following block we create an expressionset using the sample sheet and the annotations.

Annoyingly, the gff annotations are keyed in a peculiar fashion. Therefore I need to do a little work to merge them.

## Start by making locations for the biomart data
sc_annotv2[["fwd_location"]] <- paste0(sc_annotv2[["chromosome"]], "_", sc_annotv2[["start"]])
sc_annotv2[["rev_location"]] <- paste0(sc_annotv2[["chromosome"]], "_", sc_annotv2[["end"]])
## Do the same for the gff annotations
sc_gff_annotations[["fwd_location"]] <- paste0(sc_gff_annotations[["seqnames"]], "_", sc_gff_annotations[["start"]])
sc_gff_annotations[["rev_location"]] <- paste0(sc_gff_annotations[["seqnames"]], "_", sc_gff_annotations[["end"]])
sc_gff_annotations[["gff_rowname"]] <- rownames(sc_gff_annotations)
## Now merge them.
sc_fwd_annotations <- merge(sc_annotv2, sc_gff_annotations, by="fwd_location")
sc_rev_annotations <- merge(sc_annotv2, sc_gff_annotations, by="rev_location")
colnames(sc_fwd_annotations) <- c("location","transcriptID","geneID", "Description",
                                  "Type", "length", "chromosome", "strand.x", "start.x",
                                  "end.x", "location.x", "seqnames",
                                  "start.y", "end.y", "width", "strand.y", "source", "type",
                                  "score", "phase", "exon_number", "gene_id", "ID", "p_id",
                                  "protein_id", "transcript_id", "transcript_name", "tss_id",
                                  "seqedit", "location.y", "gff_rowname")
colnames(sc_rev_annotations) <- colnames(sc_fwd_annotations)
sc_all_annotations <- rbind(sc_fwd_annotations, sc_rev_annotations)
rownames(sc_all_annotations) <- make.names(sc_all_annotations[["gff_rowname"]], unique=TRUE)
sc_all_annotations <- sc_all_annotations[, c("transcriptID", "geneID", "Description", "Type",
                                             "length", "chromosome", "strand.x", "start.x", "end.x",
                                             "tss_id")]
colnames(sc_all_annotations) <- c("transcriptID", "geneID", "Description", "Type", "length",
                                  "chromosome", "strand", "start", "end", "tss_id")
sc_all_annotations[["location"]] <- paste0(sc_all_annotations[["chromosome"]], "_", sc_all_annotations[["start"]], "_", sc_all_annotations[["end"]])

sc2_expt <- create_expt(metadata="sample_sheets/all_samples.xlsx",
                        gene_info=sc_all_annotations,
                        file_column="bt2file")
## preprocessing/v2/hpgl0774/outputs/bowtie2_scerevisiae/hpgl0774_forward-trimmed.count.xz contains 7131 rows.
## preprocessing/v2/hpgl0775/outputs/bowtie2_scerevisiae/hpgl0775_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0776/outputs/bowtie2_scerevisiae/hpgl0776_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0777/outputs/bowtie2_scerevisiae/hpgl0777_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0778/outputs/bowtie2_scerevisiae/hpgl0778_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0779/outputs/bowtie2_scerevisiae/hpgl0779_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0780/outputs/bowtie2_scerevisiae/hpgl0780_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0781/outputs/bowtie2_scerevisiae/hpgl0781_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0782/outputs/bowtie2_scerevisiae/hpgl0782_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0783/outputs/bowtie2_scerevisiae/hpgl0783_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0784/outputs/bowtie2_scerevisiae/hpgl0784_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0785/outputs/bowtie2_scerevisiae/hpgl0785_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0786/outputs/bowtie2_scerevisiae/hpgl0786_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0787/outputs/bowtie2_scerevisiae/hpgl0787_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0788/outputs/bowtie2_scerevisiae/hpgl0788_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## preprocessing/v2/hpgl0789/outputs/bowtie2_scerevisiae/hpgl0789_forward-trimmed.count.xz contains 7131 rows and merges to 7131 rows.
## Bringing together the count matrix and gene information.
library(Biobase)
head(exprs(sc2_expt$expressionset))
##           hpgl0774 hpgl0775 hpgl0776 hpgl0777 hpgl0778 hpgl0779 hpgl0780 hpgl0781
## X15S_rRNA        0        0        0        0        0        0        0        0
## X21S_rRNA        0        0        0        0        0        0        0        0
## AAC1           536      477      743      443      634      188      763      414
## AAC3           126      216       93      765      152      154      102      738
## AAD10         1784     1928     2327     3869     2172      994     2472     3551
## AAD14         1054      901     1222     1863     1106      836     1307     1588
##           hpgl0782 hpgl0783 hpgl0784 hpgl0785 hpgl0786 hpgl0787 hpgl0788 hpgl0789
## X15S_rRNA        0        0        0        0        0        0        0        0
## X21S_rRNA        0        0        0        0        0        0        0        0
## AAC1           175      145      140      237      124      142      141      181
## AAC3           295      119      341      542      210      118      438     1071
## AAD10          365      589     1476     1593      352      542     1782     2082
## AAD14          542      766     1580     1814      439      795     1924     2333
head(fData(sc2_expt$expressionset))
##           transcriptID  geneID
## X15S_rRNA         <NA>    <NA>
## X21S_rRNA         <NA>    <NA>
## AAC1           YMR056C YMR056C
## AAC3           YBR085W YBR085W
## AAD10          YJR155W YJR155W
## AAD14          YNL331C YNL331C
##                                                                                                                                                                                                                                                                                                                                                                                Description
## X15S_rRNA                                                                                                                                                                                                                                                                                                                                                                             <NA>
## X21S_rRNA                                                                                                                                                                                                                                                                                                                                                                             <NA>
## AAC1                                                                           Mitochondrial inner membrane ADP/ATP translocator; exchanges cytosolic ADP for mitochondrially synthesized ATP; phosphorylated; Aac1p is a minor isoform while Pet9p is the major ADP/ATP translocator; relocalizes from mitochondrion to cytoplasm upon DNA replication stress [Source:SGD;Acc:S000004660]
## AAC3                                                  Mitochondrial inner membrane ADP/ATP translocator; exchanges cytosolic ADP for mitochondrially synthesized ATP; expressed under anaerobic conditions; similar to Aac1p; has roles in maintenance of viability and in respiration; AAC3 has a paralog, PET9, that arose from the whole genome duplication [Source:SGD;Acc:S000000289]
## AAD10     Putative aryl-alcohol dehydrogenase; similar to P. chrysosporium aryl-alcohol dehydrogenase; mutational analysis has not yet revealed a physiological role; members of the AAD gene family comprise three pairs (AAD3 + AAD15, AAD6/AAD16 + AAD4, AAD10 + AAD14) whose two genes are more related to one another than to other members of the family [Source:SGD;Acc:S000003916]
## AAD14     Putative aryl-alcohol dehydrogenase; similar to P. chrysosporium aryl-alcohol dehydrogenase; mutational analysis has not yet revealed a physiological role; members of the AAD gene family comprise three pairs (AAD3 + AAD15, AAD6/AAD16 + AAD4, AAD10 + AAD14) whose two genes are more related to one another than to other members of the family [Source:SGD;Acc:S000005275]
##                     Type length chromosome strand  start    end  tss_id
## X15S_rRNA           <NA>     NA       <NA>     NA     NA     NA    <NA>
## X21S_rRNA           <NA>     NA       <NA>     NA     NA     NA    <NA>
## AAC1      protein_coding    930       XIII     -1 387315 388244 TSS5132
## AAC3      protein_coding    924         II      1 415983 416906 TSS1609
## AAD10     protein_coding    867          X      1 727405 728271 TSS5024
## AAD14     protein_coding   1131        XIV     -1  16118  17248 TSS6941
##                     location
## X15S_rRNA               <NA>
## X21S_rRNA               <NA>
## AAC1      XIII_387315_388244
## AAC3        II_415983_416906
## AAD10        X_727405_728271
## AAD14        XIV_16118_17248
head(pData(sc2_expt$expressionset))
##          sampleid  strain condition batch originalbatch tube cbf5igv upf1igv
## hpgl0774 hpgl0774 yJD1524   wtc_wtu     r             a    f      wt      wt
## hpgl0775 hpgl0775 yJD1525   mtc_wtu     r             a    f     mut      wt
## hpgl0776 hpgl0776 yJD1745   wtc_mtu     r             a    f      wt     mut
## hpgl0777 hpgl0777 yJD1746   mtc_mtu     r             a    f     mut     mut
## hpgl0778 hpgl0778 yJD1524   wtc_wtu     r             b    g      wt      wt
## hpgl0779 hpgl0779 yJD1525   mtc_wtu     r             b    g     mut      wt
##          incubationtime
## hpgl0774            18h
## hpgl0775            18h
## hpgl0776            18h
## hpgl0777            18h
## hpgl0778            18h
## hpgl0779            18h
##                                                                                                                    genotype
## hpgl0774                                   wt ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 + CBF5 on pRS313
## hpgl0775                            d95a ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 + CBF5 D95A on pRS313
## hpgl0776        wt ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 upf1::LEU2 + CBF5 on pRS313 (yJD1524 upf1Δ)
## hpgl0777 d95a ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 upf1::LEU2 + CBF5 D95A on pRS313 (yJD1525 upf1Δ)
## hpgl0778                                   wt ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 + CBF5 on pRS313
## hpgl0779                            d95a ade2-1 can1-100 his3-11 leu2-3, 112 trp1-1 ura3-1 cbf5::TRP1 + CBF5 D95A on pRS313
##          conc bttotalreads bttotalmapped btleftmapped btrightmapped bowtiefile
## hpgl0774   NA           NA            NA           NA            NA       <NA>
## hpgl0775   NA           NA            NA           NA            NA       <NA>
## hpgl0776   NA           NA            NA           NA            NA       <NA>
## hpgl0777   NA           NA            NA           NA            NA       <NA>
## hpgl0778   NA           NA            NA           NA            NA       <NA>
## hpgl0779   NA           NA            NA           NA            NA       <NA>
##                                                                                          bt2file
## hpgl0774 preprocessing/v2/hpgl0774/outputs/bowtie2_scerevisiae/hpgl0774_forward-trimmed.count.xz
## hpgl0775 preprocessing/v2/hpgl0775/outputs/bowtie2_scerevisiae/hpgl0775_forward-trimmed.count.xz
## hpgl0776 preprocessing/v2/hpgl0776/outputs/bowtie2_scerevisiae/hpgl0776_forward-trimmed.count.xz
## hpgl0777 preprocessing/v2/hpgl0777/outputs/bowtie2_scerevisiae/hpgl0777_forward-trimmed.count.xz
## hpgl0778 preprocessing/v2/hpgl0778/outputs/bowtie2_scerevisiae/hpgl0778_forward-trimmed.count.xz
## hpgl0779 preprocessing/v2/hpgl0779/outputs/bowtie2_scerevisiae/hpgl0779_forward-trimmed.count.xz
##                                                                      intronfile
## hpgl0774 preprocessing/v2/hpgl0774/outputs/bowtie2_scerevisiae/introns.count.xz
## hpgl0775 preprocessing/v2/hpgl0775/outputs/bowtie2_scerevisiae/introns.count.xz
## hpgl0776 preprocessing/v2/hpgl0776/outputs/bowtie2_scerevisiae/introns.count.xz
## hpgl0777 preprocessing/v2/hpgl0777/outputs/bowtie2_scerevisiae/introns.count.xz
## hpgl0778 preprocessing/v2/hpgl0778/outputs/bowtie2_scerevisiae/introns.count.xz
## hpgl0779 preprocessing/v2/hpgl0779/outputs/bowtie2_scerevisiae/introns.count.xz
##                                                                                          allfile
## hpgl0774 preprocessing/v2/hpgl0774/outputs/bowtie2_scerevisiae/hpgl0774_forward-trimmed.count.xz
## hpgl0775 preprocessing/v2/hpgl0775/outputs/bowtie2_scerevisiae/hpgl0775_forward-trimmed.count.xz
## hpgl0776 preprocessing/v2/hpgl0776/outputs/bowtie2_scerevisiae/hpgl0776_forward-trimmed.count.xz
## hpgl0777 preprocessing/v2/hpgl0777/outputs/bowtie2_scerevisiae/hpgl0777_forward-trimmed.count.xz
## hpgl0778 preprocessing/v2/hpgl0778/outputs/bowtie2_scerevisiae/hpgl0778_forward-trimmed.count.xz
## hpgl0779 preprocessing/v2/hpgl0779/outputs/bowtie2_scerevisiae/hpgl0779_forward-trimmed.count.xz
##          file
## hpgl0774 null
## hpgl0775 null
## hpgl0776 null
## hpgl0777 null
## hpgl0778 null
## hpgl0779 null
library("pander")
pander(sessionInfo())

R version 3.3.3 (2017-03-06)

**Platform:** x86_64-pc-linux-gnu (64-bit)

locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=en_US.UTF-8, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=en_US.UTF-8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8 and LC_IDENTIFICATION=C

attached base packages: stats4, parallel, stats, graphics, grDevices, utils, datasets, methods and base

other attached packages: pander(v.0.6.0), TxDb.Scerevisiae.UCSC.sacCer3.sgdGene(v.3.2.2), GenomicFeatures(v.1.26.4), GenomicRanges(v.1.26.4), GenomeInfoDb(v.1.10.3), AnnotationDbi(v.1.36.2), IRanges(v.2.8.2), S4Vectors(v.0.12.2), Biobase(v.2.34.0), AnnotationHub(v.2.6.5), BiocGenerics(v.0.20.0) and hpgltools(v.2017.01)

loaded via a namespace (and not attached): Rcpp(v.0.12.11), lattice(v.0.20-35), Rsamtools(v.1.26.2), Biostrings(v.2.42.1), rprojroot(v.1.2), digest(v.0.6.12), foreach(v.1.4.3), mime(v.0.5), R6(v.2.2.1), plyr(v.1.8.4), backports(v.1.0.5), RSQLite(v.1.1-2), evaluate(v.0.10), httr(v.1.2.1), ggplot2(v.2.2.1), BiocInstaller(v.1.24.0), zlibbioc(v.1.20.0), rlang(v.0.1.1), lazyeval(v.0.2.0), curl(v.2.6), data.table(v.1.10.4), Matrix(v.1.2-10), rmarkdown(v.1.5), devtools(v.1.13.1), BiocParallel(v.1.8.2), stringr(v.1.2.0), RCurl(v.1.95-4.8), biomaRt(v.2.30.0), munsell(v.0.4.3), shiny(v.1.0.3), compiler(v.3.3.3), httpuv(v.1.3.3), rtracklayer(v.1.34.2), base64enc(v.0.1-3), htmltools(v.0.3.6), SummarizedExperiment(v.1.4.0), tibble(v.1.3.1), interactiveDisplayBase(v.1.12.0), roxygen2(v.6.0.1), codetools(v.0.2-15), XML(v.3.98-1.7), crayon(v.1.3.2), withr(v.1.0.2), GenomicAlignments(v.1.10.1), bitops(v.1.0-6), commonmark(v.1.2), grid(v.3.3.3), xtable(v.1.8-2), gtable(v.0.2.0), DBI(v.0.6-1), magrittr(v.1.5), scales(v.0.4.1), stringi(v.1.1.5), XVector(v.0.14.1), testthat(v.1.0.2), xml2(v.1.1.1), openxlsx(v.4.0.17), RColorBrewer(v.1.1-2), iterators(v.1.0.8), tools(v.3.3.3), yaml(v.2.1.14), colorspace(v.1.3-2), memoise(v.1.1.0) and knitr(v.1.16)

---
title: "Collecting S. cerevisiae annotation data."
author: "atb abelew@gmail.com"
date: "`r Sys.Date()`"
output:
 html_document:
  code_download: true
  code_folding: show
  fig_caption: true
  fig_height: 7
  fig_width: 7
  highlight: default
  keep_md: false
  mode: selfcontained
  number_sections: true
  self_contained: true
  theme: readable
  toc: true
  toc_float:
    collapsed: false
    smooth_scroll: false
---

<style>
  <!-- Document prelude revision 2017-02 -->
  body .main-container {
    max-width: 1600px;
}
</style>

```{r options, include=FALSE}
## These are the options I tend to favor
library("hpgltools")
tt <- devtools::load_all("~/hpgltools")
knitr::opts_knit$set(
    progress = TRUE,
    verbose = TRUE,
    width = 90,
    echo = TRUE)
knitr::opts_chunk$set(
    error = TRUE,
    fig.width = 8,
    fig.height = 8,
    dpi = 96)
options(
    digits = 4,
    stringsAsFactors = FALSE,
    knitr.duplicate.label = "allow")
ggplot2::theme_set(ggplot2::theme_bw(base_size=10))
set.seed(1)
ver <- "20170515"
previous_file <- "index.Rmd"
```

```{r loadme, include=FALSE}
tmp <- try(sm(loadme(filename=paste0(gsub(pattern="\\.Rmd", replace="", x=previous_file), "-v", ver, ".rda.xz"))))

rmd_file <- "annotation.Rmd"
this_save <- paste0(gsub(pattern="\\.Rmd", replace="", x=rmd_file), "-v", ver, ".rda.xz")
```

```{r render, eval=FALSE, include=FALSE}
## This block is used to render a document from within it.
rmarkdown::render(rmd_file)

## An extra renderer for pdf output
rmarkdown::render(rmd_file, output_format="pdf_document", output_options=c("skip_html"))
```

S. cerevisiae annotation data
=============================

There are a few methods of importing annotation data into R.  I will attempt
some of them in preparation for loading them into the S.cerevisiae RNASeq data.

# AnnotationHub: loading OrgDb

AnnotationHub is a newer service and has promise to be an excellent top-level resource for gathering
annotation data.

```{r data_input_genome}
tmp <- sm(library(AnnotationHub))
ah = sm(AnnotationHub())
orgdbs <- sm(query(ah, "OrgDb"))
sc_orgdb <- sm(query(ah, c("OrgDB", "Saccharomyces"))) ##   AH49589 | org.Sc.sgd.db.sqlite
sc_orgdb <- ah[["AH49589"]]

sc_orgdb
## Holy crap it worked!
sc_annotv1 <- load_orgdb_annotations(sc_orgdb,
                                     fields=c("alias", "description", "entrezid", "genename", "sgd"))
summary(sc_annotv1)
sc_annotv1 <- sc_annotv1[["genes"]]
head(sc_annotv1)
```

```{r scerevisiae_txdb}
require.auto("TxDb.Scerevisiae.UCSC.sacCer3.sgdGene")
tmp <- sm(library(TxDb.Scerevisiae.UCSC.sacCer3.sgdGene))
sc_txdb <- TxDb.Scerevisiae.UCSC.sacCer3.sgdGene
```

# Loading a genome

There is a non-zero chance we will want to use the actual genome sequence along with these
annotations.  The BSGenome packages provide that functionality.

```{r scerevisiae_bsgenome}
tt <- sm(require.auto("BSgenome.Scerevisiae.UCSC.sacCer3"))
```

# Loading a genome

There is a non-zero chance we will want to use the actual genome sequence along with these
annotations.  The BSGenome packages provide that functionality.

```{r scerevisiae_bsgenome}
tt <- sm(require.auto("BSgenome.Scerevisiae.UCSC.sacCer3"))
```

# Loading from biomart

A completely separate and competing annotation source is biomart.

```{r scerevisiae_biomart}
sc_annotv2 <- sm(get_biomart_annotations("scerevisiae"))
head(sc_annotv2)
sc_ontology <- sm(get_biomart_ontologies("scerevisiae"))
```

# Read a gff file

In contrast, it is possible to load most annotations of interest directly from the gff files used in
the alignments.

```{r genome_input}
## The old way of getting genome/annotation data
sc_gff <- "reference/scerevisiae.gff.gz"
sc_gff_annotations <- gff2df(sc_gff, type="gene")
rownames(sc_gff_annotations) <- make.names(sc_gff_annotations$transcript_name, unique=TRUE)
head(sc_gff_annotations)
```

# Putting the pieces together

In the following block we create an expressionset using the sample sheet and the
annotations.

Annoyingly, the gff annotations are keyed in a peculiar fashion.  Therefore I
need to do a little work to merge them.

```{r create_expt}
## Start by making locations for the biomart data
sc_annotv2[["fwd_location"]] <- paste0(sc_annotv2[["chromosome"]], "_", sc_annotv2[["start"]])
sc_annotv2[["rev_location"]] <- paste0(sc_annotv2[["chromosome"]], "_", sc_annotv2[["end"]])
## Do the same for the gff annotations
sc_gff_annotations[["fwd_location"]] <- paste0(sc_gff_annotations[["seqnames"]], "_", sc_gff_annotations[["start"]])
sc_gff_annotations[["rev_location"]] <- paste0(sc_gff_annotations[["seqnames"]], "_", sc_gff_annotations[["end"]])
sc_gff_annotations[["gff_rowname"]] <- rownames(sc_gff_annotations)
## Now merge them.
sc_fwd_annotations <- merge(sc_annotv2, sc_gff_annotations, by="fwd_location")
sc_rev_annotations <- merge(sc_annotv2, sc_gff_annotations, by="rev_location")
colnames(sc_fwd_annotations) <- c("location","transcriptID","geneID", "Description",
                                  "Type", "length", "chromosome", "strand.x", "start.x",
                                  "end.x", "location.x", "seqnames",
                                  "start.y", "end.y", "width", "strand.y", "source", "type",
                                  "score", "phase", "exon_number", "gene_id", "ID", "p_id",
                                  "protein_id", "transcript_id", "transcript_name", "tss_id",
                                  "seqedit", "location.y", "gff_rowname")
colnames(sc_rev_annotations) <- colnames(sc_fwd_annotations)
sc_all_annotations <- rbind(sc_fwd_annotations, sc_rev_annotations)
rownames(sc_all_annotations) <- make.names(sc_all_annotations[["gff_rowname"]], unique=TRUE)
sc_all_annotations <- sc_all_annotations[, c("transcriptID", "geneID", "Description", "Type",
                                             "length", "chromosome", "strand.x", "start.x", "end.x",
                                             "tss_id")]
colnames(sc_all_annotations) <- c("transcriptID", "geneID", "Description", "Type", "length",
                                  "chromosome", "strand", "start", "end", "tss_id")
sc_all_annotations[["location"]] <- paste0(sc_all_annotations[["chromosome"]], "_", sc_all_annotations[["start"]], "_", sc_all_annotations[["end"]])

sc2_expt <- create_expt(metadata="sample_sheets/all_samples.xlsx",
                        gene_info=sc_all_annotations,
                        file_column="bt2file")
library(Biobase)
head(exprs(sc2_expt$expressionset))
head(fData(sc2_expt$expressionset))
head(pData(sc2_expt$expressionset))
```


```{r saveme, include=FALSE}
tmp <- sm(saveme(filename=this_save))
```

```{r pander}
library("pander")
pander(sessionInfo())
```
