def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.seg_dpi = os.path.join(data_dp, 'proteomes', 'euk_seg') self.fns = os.listdir(self.seg_dpi) self.fpo = os.path.join(data_dp, 'analysis_proteomes', 'lc_composition.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.train_fpi = os.path.join(data_dp, 'train.tsv') self.k = config['score'].getint('k') self.lca = config['score'].get('lca') self.lce = config['score'].getfloat('lce')
def __init__(self, bc, organism): config = read_config.read_config() data_dp = config['fps']['data_dp'] scores_dp = os.path.join(data_dp, 'scores') self.bc = bc self.organism = organism self.fpi = os.path.join(scores_dp, 'pdb_bc_scores.tsv')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.aas = 'SGEQAPDTNKRLHVYFIMCW' self.lca = config['score'].get('lca') self.train_fp = os.path.join(data_dp, 'train.tsv') self.comp_fp = os.path.join(data_dp, 'len_comp', 'train_comp.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.tht_fpi = os.path.join(data_dp, 'experiment', '180803_ThT.xls') self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta') self.desc_fpo = os.path.join(data_dp, 'experiment', 'full_descriptions.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.label_dp = os.path.join(data_dp, 'annotations') self.enz_labels = ['hydrolase', 'isomerase', 'ligase', 'lyase', 'oxidoreductase', 'transferase'] self.labels = ['Pbody', 'RNA_binding', 'cytoplasmic_stress_granule']
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.puncta = os.path.join(data_dp, 'experiment', 'marcotte_puncta_scores.tsv') self.nopuncta = os.path.join(data_dp, 'experiment', 'marcotte_nopuncta_scores.tsv')
def __init__(self, goid, fn): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.goid = goid self.fn = fn self.fno = '{}.tsv'.format(self.fn) self.fpo = os.path.join(data_dp, 'data', 'quickgo', self.fno)
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.fpi = os.path.join(data_dp, 'experiment', '180614_glucose_starvation_2h.xlsx') self.fpo = os.path.join(data_dp, 'experiment', 'pilot.tsv') self.yeast_scores = os.path.join(data_dp, 'scores', 'all_yeast.tsv')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.bc90 = os.path.join(data_dp, 'data_bc', 'bc_train_cd90.fasta') self.pdb90 = os.path.join(data_dp, 'data_pdb', 'pdb_train_cd90.fasta') self.pdb_chain = os.path.join(data_dp, 'data_pdb', 'outside_data', 'pdb_chain_uniprot.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.train_fpi = os.path.join(data_dp, 'train.tsv') self.k = int(config['score']['k']) self.lca = str(config['score']['lca']) self.lce = float(config['score']['lce'])
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.puncta_fp = os.path.join(data_dp, 'puncta', 'marcotte', 'puncta_proteins.xlsx') self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta') self.agg_fp = os.path.join(data_dp, 'puncta', 'oconnel_agg_list')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta') self.eis_ids = os.path.join(data_dp, 'puncta', 'eisosome_annotations.txt') self.fasta_fp = os.path.join(data_dp, 'puncta', 'eisosome_fasta.fsa') self.display_fp = os.path.join(data_dp, 'puncta', 'eisosome.html')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.atg_fp = os.path.join(data_dp, 'atg', 'atg.xlsx') self.atg_out = os.path.join(data_dp, 'atg', 'atg_gene_orf_seq.tsv') self.atg_fasta = os.path.join(data_dp, 'atg', 'atg.fasta') self.atg_display = os.path.join(data_dp, 'atg', 'atg_display.html') self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta')
def main(): config = read_config.read_config() k = int(config['score']['k']) lca = str(config['score']['lca']) lce = float(config['score']['lce']) ln = LenNorm(config) lr = ln.mb_lc(k, lca, lce) print("The slope is {} and the intercept is {}".format(lr[0], lr[1]))
def __init__(self): config = read_config.read_config() data = config['fps']['data_dp'] self.fpi = os.path.join(data, 'scores', 'pdb_bc_scores.tsv') self.prot_fpi = os.path.join(data, 'scores', 'proteomes.tsv') self.yeast_fpo = os.path.join(data, 'scores', 'yeast_bc.tsv') self.human_fpo = os.path.join(data, 'scores', 'human_bc.tsv') self.prot_fpo = os.path.join(data, 'scores', 'prot.tsv')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.puncta_fp = os.path.join(data_dp, 'experiment', 'marcotte_puncta_proteins.xlsx') self.allproteins_fp = os.path.join(data_dp, 'experiment', 'marcotte_proteins.xlsx') self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) experiment_dp = os.path.join(data_dp, 'experiment') self.gfp_fp = os.path.join(experiment_dp, 'allOrfData_yeastgfp.txt') self.marcotte_fpi = os.path.join(experiment_dp, 'marcotte_puncta_proteins.xlsx') self.temp_out = os.path.join(experiment_dp, 'marcotte_notpuncta.tsv')
def __init__(self, fn_out, color=True): config = read_config.read_config() data_dp = config['fps']['data_dp'] self.k = config['score'].getint('k') self.lca = config['score'].get('lca') self.lce = config['score'].getfloat('lce') self.fp_out = os.path.join(data_dp, 'display', fn_out) self.color = color
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.exp_dp = os.path.join(data_dp, 'expression_files_for_S3', 'Gasch_2000_PMID_11102521') self.exp_fp = os.path.join( self.exp_dp, '2010.Gasch00_stationaryPhase(y14).flt.knn.avg.pcl') self.puncta_fpi = os.path.join(data_dp, 'experiment', 'marcotte_puncta_scores.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) pdb_an_dp = os.path.join(data_dp, 'pdb_analysis') self.fpi = os.path.join(pdb_an_dp, 'pdb_len_norm.tsv') self.lc_m = 0.066213297264721263 self.lc_b = 1.7520712972708843 self.lc_b_up = 16.5 self.grey_b = 36.5
def __init__(self): config = read_config.read_config() data = config['fps']['data_dp'] bio_dp = os.path.join(data, 'biogrid') self.bio_fp = os.path.join(bio_dp, 'BIOGRID-ORGANISM-Saccharomyces_cerevisiae_S288c-3.4.157.mitab.txt') self.pbody_fp = os.path.join(bio_dp, 'Pbody_annotations.txt') self.interactions_fp = os.path.join(bio_dp, 'pbody.tsv') self.yeast_scores = os.path.join(bio_dp, 'orf_pbody_scores.tsv') self.yeast_fasta = os.path.join(bio_dp, 'orf_trans.fasta')
def __init__(self): config = read_config.read_config() data_dp = config['fps']['data_dp'] bc_dp = os.path.join(data_dp, 'data_bc') self.bc_an_dp = os.path.join(data_dp, 'bc_analysis') # Use fasta file with all bc sequences self.fasta = os.path.join(bc_dp, 'quickgo_bc.fasta') self.bc_ss = os.path.join(bc_dp, 'quickgo_bc.xlsx') self.bc_score_fp = os.path.join(self.bc_an_dp, 'bc_all_score.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.bc_fp = os.path.join(data_dp, 'bc_analysis', 'bc_all_score.tsv') self.red_motif_fp = os.path.join(data_dp, 'kelil', 'rep_motifs_red.tsv') self.body_dp = os.path.join(data_dp, 'bc_analysis') self.kelil_dp = os.path.join(data_dp, 'kelil') self.allbc_out = os.path.join(data_dp, 'kelil', 'bc_all_motifs.tsv')
def __init__(self): config = read_config.read_config() self.data_dp = config['fps']['data_dp'] self.bc_dp = os.path.join(self.data_dp, 'bc_analysis', 'P_Body_score.tsv') self.fp_out = os.path.join(self.data_dp, 'display', 'Pbody_human.html') self.k = config['score'].getint('k') self.lca = config['score'].get('lca') self.lce = config['score'].getfloat('lce')
def __init__(self): config = read_config.read_config() data = config['fps']['data_dp'] self.train_fpi = os.path.join(data, 'train.tsv') prot_dp = os.path.join(data, 'proteomes') self.bc_dp = os.path.join(data, 'bc_analysis') self.yeast_fp = os.path.join(prot_dp, 'UP000002311_559292_Yeast.fasta') self.human_fp = os.path.join(prot_dp, 'UP000005640_9606_Human.fasta') self.fpo = os.path.join(data, 'scores', 'pdb_bc_scores.tsv')
def __init__(self): self.config = read_config.read_config() self.data_dp = self.config['fps']['data_dp'] self.pdb_dp = os.path.join(self.data_dp, 'pdb_prep') self.pdb_an_dp = os.path.join(self.data_dp, 'pdb_analysis') self.an_fpi = os.path.join(self.pdb_dp, 'pdb_analysis.tsv') self.miss_fp = os.path.join(self.pdb_an_dp, 'miss_in_out.tsv') self.k = 6 self.lce = 1.6 self.lca = 'SGEQAPDTNKR'
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.marcotte_fpi = os.path.join(data_dp, 'experiment', 'marcotte_puncta_proteins.xlsx') self.orf_trans = os.path.join(data_dp, 'proteomes', 'orf_trans.fasta') self.puncta_fpo = os.path.join(data_dp, 'experiment', 'marcotte_puncta_scores.tsv') self.npuncta_fpo = os.path.join(data_dp, 'experiment', 'marcotte_nopuncta_scores.tsv')
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) pdb_dp = os.path.join(data_dp, 'pdb_prep') pdb_an_dp = os.path.join(data_dp, 'pdb_analysis') self.norm_fpi = os.path.join(pdb_dp, 'pdb_norm_cd100.tsv') self.fpo = os.path.join(pdb_an_dp, 'pdb_len_norm.tsv') self.k = int(config['score']['k']) self.lca = str(config['score']['lca']) self.lce = float(config['score']['lce'])
def __init__(self): config = read_config.read_config() data_dp = os.path.join(config['fps']['data_dp']) self.fpi = os.path.join(data_dp, '..', 'drosophila_llps', 'candidate_drosophila.fasta') self.cand_fpo = os.path.join(data_dp, '..', 'drosophila_llps', 'candidate_drosophila.tsv') self.all_fpi = os.path.join(data_dp, '..', 'drosophila_llps', 'all_drosophila.fasta') self.all_fpo = os.path.join(data_dp, '..', 'drosophila_llps', 'all_drosophila.tsv')