data-raw/data_internal.R

In hochwagenlab/hwglabr: Collection of R functions used in the Hochwagen Lab

#------------------------------------------------------------------------------#
#                                                                              #
#                 Generation of data internal to the package                   #
#                                                                              #
#------------------------------------------------------------------------------#

# Get all data frames and then generate internal package data
# at the end of the script (/R/sysdata.rda)


#------------------------------------------------------------------------------#
#             First iteration of convergent intergenic regions                 #
#                            (Now deprecated)                                  #
# S288C genome
# Import data file, originally generated using:
# "/Volumes/LabShare/Luis/LabWork/Scripts/2015.10_H3k79me3_transcription.R"
path <- '/Users/luis/Google_Drive_NYU/LabShare_Luis/LabWork/2015.05_dot1_rec8dot1/2015.10_H3K79me3_transcripts/'
S288C_conv <- read.table(paste0(path, 'conv_midpoints_rpkm.txt'),
                         header = TRUE, stringsAsFactors = FALSE)
# Remove info about transcription:
S288C_conv <- S288C_conv[, 1:6]

# SK1 genome
# Import data file, originally generated using:
# /Volumes/LabShare/Luis/LabWork/Scripts/2015.11_convMidpointsSK1.R
path <- '/Users/luis/Google_Drive_NYU/LabShare_Luis/LabWork/GenomeSequences/SK1/'
SK1_conv <- read.table(paste0(path, 'conv_midpoints_SK1.txt'),
                       header = TRUE, stringsAsFactors = FALSE)


#------------------------------------------------------------------------------#
#                       New intergenic region data                             #
#                         (Conv, div and tandem)                               #
# The intergenic region coordinate files were generated (by Luis and Tovah) using
# the scripts found at: '/Volumes/LabShare/Luis/LabWork/GenomeSequences/hwglabr/'
# 1. Import data file
path <- '/Volumes/LabShare/GenomeSequences/hwglabr/'
S288C_conv_midpoint_dist <- read.table(paste0(path, 'S288C_conv_midpoint_dist.txt'),
                                       header = TRUE, stringsAsFactors = FALSE)
S288C_div_midpoint_dist <- read.table(paste0(path, 'S288C_div_midpoint_dist.txt'),
                                      header = TRUE, stringsAsFactors = FALSE)
S288C_tand_midpoint_dist <- read.table(paste0(path, 'S288C_tand_midpoint_dist.txt'),
                                       header = TRUE, stringsAsFactors = FALSE)
SK1_conv_midpoint_dist <- read.table(paste0(path, 'SK1_conv_midpoint_dist.txt'),
                                     header = TRUE, stringsAsFactors = FALSE)
SK1_div_midpoint_dist <- read.table(paste0(path, 'SK1_div_midpoint_dist.txt'),
                                    header = TRUE, stringsAsFactors = FALSE)
SK1_tand_midpoint_dist <- read.table(paste0(path, 'SK1_tand_midpoint_dist.txt'),
                                     header = TRUE, stringsAsFactors = FALSE)


#------------------------------------------------------------------------------#
#                               Centromeres                                    #
# SK1 info based on Keeney lab genome sequence and annotation
SK1cen <- data.frame("Chromosome" = c("chr01","chr02","chr03","chr04","chr05",
                                     "chr06","chr07","chr08","chr09","chr10",
                                     "chr11","chr12","chr13","chr14","chr15",
                                     "chr16"),
                     "Start" = c(137832, 226711, 128699, 463204, 157003, 162815,
                                 505440, 95031, 346215, 415648, 452723, 137738,
                                 249103, 616840, 307236, 553355),
                     "End" = c(137948, 226826, 128779, 463321, 157119, 162931,
                               505558, 95147, 346330, 415764, 452838, 137855,
                               249221, 616956, 307353, 553467),
                     "Mid" = c(137890, 226768, 128739, 463262, 157061, 162873,
                               505499, 95089, 346272, 415706, 452780, 137796,
                               249162, 616898, 307294, 553411),
                     "LenChr" = c(203893, 794508, 342718, 1490682, 602514,
                                  284456, 1067526, 544538, 435585, 719294,
                                  687260, 1008248, 908607, 812465, 1054033,
                                  921188))

SK1cen$Chromosome <- as.character(SK1cen$Chromosome)

# S288C
path <- '/Users/luis/Google_Drive_NYU/LabShare_Luis/LabWork/GenomeSequences/'
S288C_gff <- read.table(paste0(path, 'saccharomyces_cerevisiae_R64-1-1_20110208.gff'),
                        fill = TRUE, stringsAsFactors = FALSE)
S288C_gff <- S288C_gff[1:16406, ]
S288Ccen <- S288C_gff[S288C_gff[, 3] == 'centromere', c(1, 4:5)]
names(S288Ccen) <- c('Chromosome', 'Start', 'End')
S288Ccen$Mid <- floor(S288Ccen$Start +  (S288Ccen$End - S288Ccen$Start) / 2)
S288Ccen$LenChr <- S288C_gff[S288C_gff[, 3] == 'chromosome', 5][1:16]


#------------------------------------------------------------------------------#
#                               SKI rosetta                                    #
path <- '/Users/luis/Google_Drive_NYU/LabShare_Luis/LabWork/GenomeSequences/'
SK1rosetta <- read.table(paste0(path, 'SK1rosetta_R64.txt'),
                         header = TRUE, sep = '\t')

#------------------------------------------------------------------------------#
#                                GFF files                                     #
#               Used by opening_act() to run signal_at_orf()                   #
s288C_gff <- '/Volumes/LabShare/GenomeSequences/s288C_annotation_R64_modified.gff'
SK1_gff <- '/Volumes/LabShare/GenomeSequences/SK1_MvO_V1___GENOME/SK1_annotation/SK1_annotation_modified_v2.gff'
s288C_gff <- hwglabr::gff_read(s288C_gff)
# Further parse attributes field to get gene ID only
SK1_gff <- hwglabr::gff_read(SK1_gff)
SK1_gff$attributes <- hwglabr::gff_get_attribute(SK1_gff$attributes, 'ID')

#------------------------------------------------------------------------------#
#                            Spo11 DSB hotspots                                #
#                           Used by opening_act()                              #

# For details of data generation see:
# "Volumes/LabShare/HTGenomics/HiSeqOutputs/2015-08-21_Thacker2014_Spo11Hotspots/Creating_spo11_SacCer3_Pan2011_WT1_fixedbedgraph.R"
# Source of data: nature13120-s2_SacCer2.xls from Thacker 2014 paper.
# Convert to bed file. Run through UCSC liftover
# (https://genome.ucsc.edu/cgi-bin/hgLiftOver) to convert from SacCer2 to SacCer3
# Realign liftover bed information and WT1 column from XLS file to make the bedgraph.
file <- '/Volumes/LabShare/GenomeSequences/hwglabr/spo11_SacCer3_Pan2011hotspot_WT1_fixed.bedgraph'
Spo11_DSBs <- read.table(file)


#------------------------------------------------------------------------------#
#                            Red1 summits in WT                                #
#                           Used by opening_act()                              #

### On HPC:
# qsub -v CHIP="AH119B-053013_TGACCA_L008_R1_001.fastq",INPUT="AH119A-053013_CGATGT_L008_R1_001.fastq",TAGC="AH119B-053013",TAGI="AH119A-053013",GEN="SacCer3",PEAK=F,BDG=F ~/Pipeline/MACS2_pipeline_v2.sh
# qsub -v CHIP="AH119C-040114_GTCCGC_L001_R1_001.fastq",INPUT="AH119A-040114_CCGTCC_L001_R1_001.fastq",TAGC="AH119C-040114",TAGI="AH119A-040114",GEN="SacCer3",PEAK=F,BDG=F ~/Pipeline/MACS2_pipeline_v2.sh
# qsub -v CHIP="AH119B-053013-SacCer3-2mis-PM.sam:AH119C-040114-SacCer3-2mis-PM.sam",INPUT="AH119A-053013-SacCer3-2mis-PM.sam:AH119A-040114-SacCer3-2mis-PM.sam",REP="AH119BC",BDG=F ~/Pipeline/MACS2_pipeline_v2.sh
# In R: [remove summits with Q-values(-log10) below 20]
# bed <- read.table("AH119BC-SacCer3-2mis-PM-reps-M5_summits.bed")
# Q20<- bed[which(bed[,5]>=20),]
# write.table(Q20,file="AH119BC-SacCer3-2mis-PM-reps-M5_Q20_summits.bed",quote=F,sep="\t",row.names=F,col.names=F)
file <- '/Volumes/LabShare/GenomeSequences/hwglabr/AH119BC-SacCer3-2mis-PM-reps-M5_Q20_summits.bed'
Red1_summits <- read.table(file)

#------------------------------------------------------------------------------#
#------------------------------------------------------------------------------#
#                           Add all data to package                            #
#                             (as internal data)                               #

# Determine the best compression for the data files
tools::checkRdaFiles('R/')  # Suggests 'bzip2'

setwd('/Users/luis/Google_Drive_NYU/LabShare_Luis/LabWork/Code/Rpackages/hwglabr')
devtools::use_data(S288C_conv_midpoint_dist,
                   S288C_div_midpoint_dist,
                   S288C_tand_midpoint_dist,
                   SK1_conv_midpoint_dist,
                   SK1_div_midpoint_dist,
                   SK1_tand_midpoint_dist,
                   S288C_conv,
                   SK1_conv,
                   S288Ccen,
                   SK1cen,
                   SK1rosetta,
                   s288C_gff,
                   SK1_gff,
                   Spo11_DSBs,
                   Red1_summits,
                   internal = TRUE, overwrite = TRUE, compress = "bzip2")