R scripts used to determine the load of deleterious mutations in domestication and wild sunflowers
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README
alignments_stats.R
bwa.R
dprovean.R
missingdata_check_alignments_fractions.R
pi.R
plotting.R
provean_afterprovean.R
provean_aftersift.R
provean_sift.R
recomrate.R
samtools_mpileup.R
samtools_mpileup_aftermpileup.R
snp_parser.R
syn_nonsyn_vII.R
table_S1.R
wprovean.R

README

###This is a readme file that list what all the scripts do and in what order they should be used


#aligning reads
#align with bwa
#generate sam/bam files. index files with samtools
#filter out bad reads and do local realignments with gatk.
bwa.R

#calling snps with samtools mpileup
samtools_mpileup.R

#cleaning up and parsing the snps.
samtools_mpileup_aftermpileup.R
snp_parser.R

#are the non-synynomus snps deleterious. there are 2 alternative versions (d and w) depending on the reference (domesticated only or wild only)
#See methods in the paper for more info. but essentially, you should not use dprovean.R and wprovean.R, they might not be up-to-date.
provean_sift.R # this also runs SIFT
dprovean.R
wprovean.R

#parsing the provean/sift results
provean_afterprovean.R
provean)aftersift.R

#are snps syn. non-syn. non-coding?
syn_nonsyn_vII.R

#calculate nucleotide diversity using SITES from Jody Hey's lab
pi.R

#redo figure 1, but with different missing data thresholds.
missingdata_check_alignments_fractions.R

#find out the effect of recombination rate
recomrate.R

#plotting all the Figures, unless a figure is specified in another script
plotting.R

#generate table S1 and some other alignment stats...
table_S1.R