## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
fig.width = 6,
fig.height = 5.5,
collapse = TRUE,
warning = FALSE,
comment = "#>"
)
## ----load_data, eval=FALSE----------------------------------------------------
# library(movAPA)
# pac=read.csv('arabidopsis_thaliana.SRP093950_amp.high_confidence.PAC.annotation.tpm.csv', stringsAsFactors =F)
#
# ## Rename annotation columns.
# ## In a PACdataset, the annotation column names must be named as (gene/gene_type/ftr/ftr_start/ftr_end/UPA_start/UPA_end).
# ## Other non-sample columns will be also retained in the @anno slot of the PACdataset.
# pac=dplyr::rename(pac, UPA_start = 'start', UPA_end='end', gene_type='biotype')
# colnames(pac)
#
# ## Describe the sample columns and corresponding group(s) in a data.frame
# colData=as.data.frame(matrix(c('Amp','Amp','Amp'), ncol=1, dimnames=list(paste0('Amp311_R',1:3), 'group')))
#
# ## Read the PAC file into a PACdataset
# PACds=readPACds(pacFile=pac, colDataFile=colData, noIntergenic=FALSE, PAname='PA')
#
# PACds
## ----eval=FALSE---------------------------------------------------------------
# # For example, users can remove internal priming artifacts
# library("BSgenome.Athaliana.TAIR.TAIR9")
# bsgenome <- BSgenome.Athaliana.TAIR.TAIR9
#
# # Please make sure the chr name of your PAC data is the same as the BSgenome.
# seqnames(bsgenome)
#
# PACdsIP=removePACdsIP(PACds, bsgenome, returnBoth=TRUE,
# up=-10, dn=10, conA=6, sepA=7)
# length(PACdsIP$real)
# length(PACdsIP$ip)
#
# # Base compostions and k-grams
# faFiles=faFromPACds(PACds, bsgenome, what='updn', fapre='updn',
# up=-300, dn=100, byGrp='ftr')
## ----fig.dim=c(6,4), eval=FALSE-----------------------------------------------
# faFiles=c("updn.3UTR.fa", "updn.CDS.fa", "updn.intergenic.fa", "updn.intron.fa")
# ## Plot single nucleotide profiles using the extracted sequences and merge all plots into one.
# plotATCGforFAfile (faFiles, ofreq=FALSE, opdf=FALSE,
# refPos=301, mergePlots = TRUE)
## ----load_data2, eval=FALSE---------------------------------------------------
# ## Read a BED file
# pac=read.table('arabidopsis_thaliana.SRP093950_amp.high_confidence.PAC.bed',
# header=F, stringsAsFactors =F)
# head(pac)
#
# # We only keep the chr/strand/coord, here we used the start position as the coord.
# colnames(pac)=c('chr','coord','x','dot','strand')
# pac=pac[,c('chr','strand','coord')]
#
# # We don't have any expression level of the sample,
# # so we only read the PAC list and set the expression as 1.
# ## Read the PAC file into a PACdataset
# PACds=readPACds(pacFile=pac, colDataFile=NULL, noIntergenic=FALSE, PAname='PA')
# PACds
## ----eval=FALSE---------------------------------------------------------------
# # Please download the genome annotation file of Arabidopsis TAIR 10
# # in gff3 format from the tair website.
# athGFF="Arabidopsis_thaliana.TAIR10.42.gff3"
#
# # First we parse the gff3 file.
# gff=parseGff(athGFF)
#
# # Please make sure the chromosome name of your PAC data
# # is the same as the gff file (and the BSgenome)
# head(gff$anno.need)
#
# # You can also save the parsed gff file as an rda object for further use.
# # save(gff, file='TAIR10.gff.rda')
# # Annotate the PAC data
# PACds=annotatePAC(PACds, gff)
# PACds
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