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')
