__doc__=""" pliu 20150511 python module for all parameters, input arguments """ class Param: IDR_THRESHOLD = 0.05 N_PEAK = 300000 PEAK_TYPE = '-savr' EXCLUSION_ZONE = '-500:85' ## Anshul recommend -500:85 TRAINING_GENE_MIN_LEN = 1003 TRAINING_MIN_MAPPABILITY = 0.8 FLANKING_WIDTH = 500 ## in nt, flanking region around TSS and TES INFORMATIVE_DATA_MAX_P_VALUE = 0.01 ## external data set is informative if ## p-value is not more than this value def __init__(self): self.argdict = None ## has to be in the same naming convention as prsem-calculate-expression self.num_threads = None self.chipseq_target_read_files = None self.chipseq_control_read_files = None self.chipseq_read_files_multi_targets = None self.chipseq_bed_files_multi_targets = None self.cap_stacked_chipseq_reads = None self.n_max_stacked_chipseq_reads = None self.bowtie_path = None self.chipseq_peak_file = None self.mappability_bigwig_file = None self.partition_model = None self.gibbs_burnin = None self.gibbs_number_of_samples = None self.gibbs_sampling_gap = None self.quiet = False ## arguments self.ref_fasta = None self.ref_name = None self.sample_name = None self.stat_name = None self.imd_name = None ## path and pRSEM scripts self.temp_dir = None ## dir to save RSEM/pRSEM intermediate files self.prsem_scr_dir = None ## pRSEM scripts dir self.prsem_rlib_dir = None ## place to install pRSEM required R libraries ## genome reference: training set isoforms self.fall_exon_crd = None self.fall_tr_crd = None ## tr info + mappability self.ftraining_tr_crd = None ## training set tr ## ChIP-seq self.chipseqexperiment_target = None ## reference to ChIP-seq experiment self.chipseqexperiment_control = None ## reference to ChIP-seq experiment self.chipseq_rscript = None ## full name of process-chipseq.R self.filterSam2Bed = None ## full name of filterSam2Bed binary self.spp_tgz = None self.spp_script = None self.idr_scr_dir = None self.idr_script = None self.fgenome_table = None self.fidr_chipseq_peaks = None self.fall_chipseq_peaks = None self.fchipseq_peaks = None ## full name of user supplied ChIP-seq peak ## file, otherwise is fidr_chipseq_peaks self.chipseq_target_fraglen = None ## spp-estimated fragment length self.fsppout_target = None ## full name of SPP output ## this implementation needs to be refined since ## the var is define in both Param and ChIPSeqExp self.fchipseq_target_signals = None self.fchipseq_control_signals = None ## transcripts and RNA-seq self.transcripts = None ## reference to all transcripts to be quantified self.genes = None ## reference to all genes to be quantified self.rnaseq_rscript = None ## fullname of R script for dealing RNA-seq self.fti = None ## RSEM's reference .ti file self.bigwigsummary_bin = None ## bigWigSummary binary self.fall_tr_features = None ## file for all isoforms' features self.fall_tr_prior = None ## file for all isoforms' priors self.fisoforms_results = None ## file for RSEM .isoforms.results self.fpvalLL = None ## file for p-value on if informative ## and for log-likelihood self.fall_pvalLL = None ## file to store all the p-val and log-likelihood ## for multiple external data sets self.targetid2fchipseq_alignment = {} self.finfo_multi_targets = None self.flgt_model_multi_targets = None ## for testing procedure self.targetids = [] def __str__(self): ss = [ "%-33s %s\n" % (key, val) for (key, val) in list(self.argdict.items())] + \ [ "%-33s %s\n" % ('RSEM_temp_dir', self.temp_dir ) ] + \ [ "%-33s %s\n" % ('pRSEM_scr_dir', self.prsem_scr_dir) ] return ''.join(ss) @classmethod def initFromCommandLineArguments(cls, argdict): import os prm = cls() prm.argdict = argdict for (key, val) in list(argdict.items()): setattr(prm, key, val) if prm.imd_name is not None: prm.temp_dir = os.path.split(prm.imd_name)[0] + '/' prm.prsem_scr_dir = os.path.dirname(os.path.realpath(__file__)) + '/' prm.prsem_rlib_dir = prm.prsem_scr_dir + 'RLib/' if not os.path.exists(prm.prsem_rlib_dir): os.mkdir(prm.prsem_rlib_dir) ## genome reference: pRSEM training set isoforms prm.fall_exon_crd = prm.ref_name + '_prsem.all_exon_crd' prm.fall_tr_crd = prm.ref_name + '_prsem.all_tr_crd' prm.ftraining_tr_crd = prm.ref_name + '_prsem.training_tr_crd' ## ChIP-seq prm.chipseq_rscript = prm.prsem_scr_dir + 'process-chipseq.R' prm.filterSam2Bed = prm.prsem_scr_dir + 'filterSam2Bed' prm.spp_tgz = prm.prsem_scr_dir + 'phantompeakqualtools/spp_1.10.1.tar.gz' prm.spp_script = prm.prsem_scr_dir + 'phantompeakqualtools/run_spp.R' prm.idr_scr_dir = prm.prsem_scr_dir + 'idrCode/' prm.idr_script = prm.idr_scr_dir + 'batch-consistency-analysis.r' prm.fgenome_table = prm.ref_name + '.chrlist' if prm.temp_dir is not None: prm.fsppout_target = prm.temp_dir + 'target_phantom.tab' prm.fchipseq_target_signals = prm.temp_dir + 'target.tagAlign.gz' prm.fchipseq_control_signals = prm.temp_dir + 'control.tagAlign.gz' prm.fidr_chipseq_peaks = "%s/%s" % (prm.temp_dir, 'idr_target_vs_control.regionPeak.gz') ## have to name it this way due to run_spp.R's wired naming convention ## this names depens on the next two names prm.fall_chipseq_peaks = "%s/%s" % (prm.temp_dir, 'target.tagAlign_VS_control.tagAlign.regionPeak.gz') if prm.chipseq_peak_file is not None: prm.fchipseq_peaks = prm.chipseq_peak_file else: prm.fchipseq_peaks = prm.fidr_chipseq_peaks ## transcripts and RNA-seq prm.rnaseq_rscript = prm.prsem_scr_dir + 'process-rnaseq.R' prm.fti = prm.ref_name + '.ti' prm.ffasta = prm.ref_name + '.transcripts.fa' prm.bigwigsummary_bin = prm.prsem_scr_dir + 'bigWigSummary' #prm.fall_exon_crd = prm.imd_name + '_prsem.all_exon_crd' #prm.fall_tr_crd = prm.imd_name + '_prsem.all_tr_crd' #prm.ftraining_tr_crd = prm.imd_name + '_prsem.training_tr_crd' if prm.sample_name is not None: ## for calc-expr prm.fall_tr_gc = prm.imd_name + '_prsem.all_tr_gc' prm.fall_tr_features = prm.stat_name + '_prsem.all_tr_features' prm.fall_tr_prior = prm.stat_name + '_prsem.all_tr_prior' prm.fpvalLL = prm.stat_name + '_prsem.pval_LL' prm.fisoforms_results = prm.sample_name + '.isoforms.results' prm.fall_pvalLL = prm.sample_name + '.all.pval_LL' ## for multiple external data sets prm.finfo_multi_targets = prm.temp_dir + 'multi_targets.info' prm.flgt_model_multi_targets = prm.stat_name + '_prsem.lgt_mdl.RData' return prm def initFromCommandLineArguments(argdict): return Param.initFromCommandLineArguments(argdict)