Background frequencies

from katlas.core import *
import pandas as pd
df = Data.get_ks_unique()
df.head()
sub_site num_kin bin sub_genes site_seq source_combine acceptor O00141_SGK1 O00238_BMPR1B O00311_CDC7 ... Q9Y2K2_SIK3 Q9Y2U5_MAP3K2 Q9Y3S1_WNK2 Q9Y463_DYRK1B Q9Y4K4_MAP4K5 Q9Y572_RIPK3 Q9Y5S2_CDC42BPB Q9Y6E0_STK24 Q9Y6M4_CSNK1G3 Q9Y6R4_MAP3K4
0 A0A2R8Y4L2_S158 1 1 HNRNPA1L3 HNRNPA1P48 TDRGSGKKRGFAFVTFDDHDsVDKIVIQKYHTVNGHNCEVR Sugiyama S 0 0 0 ... 0 0 0 0 0 0 0 0 0 0
1 A0A2R8Y4L2_S22 3 2~10 HNRNPA1L3 HNRNPA1P48 SKSEsPKEPEQLRKLFIGGLsFEtTDESLRSHFEQWGTLTD Sugiyama S 0 0 0 ... 0 0 0 0 0 0 0 0 0 0
2 A0A2R8Y4L2_S6 3 2~10 HNRNPA1L3 HNRNPA1P48 _______________MSKSEsPKEPEQLRKLFIGGLsFEtT Sugiyama S 0 0 0 ... 0 0 0 0 0 0 0 0 0 0
3 A0A2R8Y4L2_S95 65 11~100 HNRNPA1L3 HNRNPA1P48 RPHKVDGRVVEPKRAVSREDsQRPDAHLTVKKIFVGGIKED Sugiyama S 0 1 0 ... 0 1 0 0 1 0 0 0 0 0
4 A0A2R8Y4L2_T25 3 2~10 HNRNPA1L3 HNRNPA1P48 EsPKEPEQLRKLFIGGLsFEtTDESLRSHFEQWGTLTDCVV Sugiyama T 0 0 0 ... 0 0 0 0 0 0 0 0 0 0

5 rows × 462 columns

PSSMs - ks dataset

def get_bg_dict(df, acceptor, seq_col='site_seq'):
    site = df[df.acceptor.isin(list(acceptor))].copy()
    site_pssm = get_prob(site, seq_col)
    return flatten_pssm(site_pssm, True)
acceptors = ['S','T','Y','ST','STY']
index_names = 'KS Dataset Background: ' + pd.Series(acceptors)
bg_pssms = pd.DataFrame([get_bg_dict(df,acceptor) for acceptor in acceptors],index=index_names)
def get_site_cnt(df, acceptor, seq_col='site_seq'):
    site = df[df.acceptor.isin(list(acceptor))].copy()
    return len(site)
cnt = {name:get_site_cnt(df,acceptor) for acceptor,name in zip(acceptors,index_names)}
plot_logos(bg_pssms,cnt,prefix='')
save_pdf('fig/background_ks.pdf')

PSSMs - human phosphoproteome

human = Data.get_human_site()
human['acceptor']=human.site.str[0]
human.head(1)
substrate_uniprot substrate_genes site source AM_pathogenicity substrate_sequence substrate_species sub_site substrate_phosphoseq position site_seq acceptor
0 A0A024R4G9 C19orf48 MGC13170 hCG_2008493 S20 psp NaN MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSH... Homo sapiens (Human) A0A024R4G9_S20 MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTRTWLLSH... 20 _MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTR S 
index_names2 = 'Human Phosphoproteome Background: ' + pd.Series(acceptors)
bg_pssms_human = pd.DataFrame([get_bg_dict(human,acceptor) for acceptor in acceptors],index=index_names2)
bg_pssms_human
-20P -20G -20A -20C -20S -20T -20V -20I -20L -20M ... 20H 20K 20R 20Q 20N 20D 20E 20s 20t 20y
Human Phosphoproteome Background: S 0.08364 0.06732 0.07243 0.01298 0.06843 0.04076 0.04860 0.03262 0.08046 0.01853 ... 0.02240 0.06643 0.06452 0.04737 0.03316 0.05179 0.07982 0.04460 0.01317 0.00367
Human Phosphoproteome Background: T 0.07986 0.06436 0.07476 0.01194 0.06270 0.04093 0.05299 0.03346 0.07854 0.02181 ... 0.02007 0.07009 0.06264 0.04805 0.03220 0.05181 0.07866 0.04366 0.01702 0.00485
Human Phosphoproteome Background: Y 0.07390 0.06714 0.07310 0.01602 0.05840 0.03946 0.05178 0.04145 0.08741 0.02026 ... 0.02177 0.06572 0.05960 0.04994 0.03130 0.05538 0.07811 0.03470 0.01619 0.01660
Human Phosphoproteome Background: ST 0.08279 0.06666 0.07295 0.01275 0.06714 0.04079 0.04959 0.03281 0.08003 0.01927 ... 0.02188 0.06725 0.06410 0.04752 0.03295 0.05180 0.07956 0.04439 0.01403 0.00394
Human Phosphoproteome Background: STY 0.08221 0.06669 0.07296 0.01296 0.06657 0.04071 0.04973 0.03338 0.08052 0.01933 ... 0.02187 0.06715 0.06381 0.04768 0.03284 0.05203 0.07946 0.04377 0.01417 0.00475

5 rows × 943 columns

all_pssms = pd.concat([bg_pssms,bg_pssms_human])
# all_pssms.to_parquet('~/katlas/dataset/CDDM/ks_background.parquet')

Accessible through Data.get_ks_background

cnt_human = {name:get_site_cnt(human,acceptor) for acceptor,name in zip(acceptors,index_names2)}
cnt.update(cnt_human)
cnt
{'KS Dataset Background: S': 15981,
 'KS Dataset Background: T': 6762,
 'KS Dataset Background: Y': 7068,
 'KS Dataset Background: ST': 22743,
 'KS Dataset Background: STY': 29811,
 'Human Phosphoproteome Background: S': 86995,
 'Human Phosphoproteome Background: T': 25091,
 'Human Phosphoproteome Background: Y': 7869,
 'Human Phosphoproteome Background: ST': 112086,
 'Human Phosphoproteome Background: STY': 119955}
plot_logos(bg_pssms_human,cnt,prefix='')
save_pdf('fig/background_human.pdf')