Preprocess

Functions to preprocess sequence to prepare kinase substrate dataset

Setup

from katlas.utils import *

Commons

source

save_show

 save_show (path=None)

Show plot or save path

	Type	Default	Details
path	NoneType	None	image path, e.g., img.svg, if not None, will save, else plt.show()

source

get_path

 get_path (dir_path, fname)

Ensure the directory exists and return the full file path.

get_path('~/img/folder','test.svg')

source

get_diff

 get_diff (df1, df2, col1, col2=None)

Get non-overlap parts of two dataframes.

df1 = pd.DataFrame({'gene': ['A', 'B', 'C']})
df2 = pd.DataFrame({'gene': ['B', 'C', 'D']})

df1_unq, df2_unq = get_diff(df1, df2, 'gene')

df1_unq

	gene
0	A

df2_unq

	gene
2	D

Checker

In many phosphorylation datsets, there are amino acids in the site sequence that are in lower case but does not belong to s/t/y. Also, there are uncommon amino acids such as U or O that appear in the sequence. Therefore, it is essential to convert the sequence string for kinase ranking.

source

check_seq

 check_seq (seq)

Convert non-s/t/y characters to uppercase and replace disallowed characters with underscores.

try:
    check_seq('aaadaaa')
except Exception as e:
    print(e)

aaadaaa has d at position 3; need to have one of 's', 't', or 'y' in the center

check_seq('AAkUuPSFstTH') # if the center amino acid does not belong to sty/STY, will raise an error

'AAK__PSFstTH'

source

check_seqs

 check_seqs (seqs:pandas.core.series.Series)

Convert non-s/t/y to upper case & replace with underscore if the character is not in the allowed set

source

check_seq_df

 check_seq_df (df, col)

Convert non-s/t/y to upper case & replace with underscore if the character is not in the allowed set

df=Data.get_human_site()
df.head()

	substrate_uniprot	substrate_genes	site	source	AM_pathogenicity	substrate_sequence	substrate_species	sub_site	substrate_phosphoseq	position	site_seq
0	A0A024R4G9	C19orf48 MGC13170 hCG_2008493	S20	psp	NaN	MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSH...	Homo sapiens (Human)	A0A024R4G9_S20	MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTRTWLLSH...	20	_MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTR
1	A0A075B6Q4	None	S24	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S24	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	24	QKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPG
2	A0A075B6Q4	None	S35	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S35	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	35	EDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKTHRAIADHLF
3	A0A075B6Q4	None	S57	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S57	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	57	EDCMSVPGKTHRAIADHLFWsEETKSRFTEYsMTssVMRRN
4	A0A075B6Q4	None	S68	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S68	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	68	RAIADHLFWsEETKSRFTEYsMTssVMRRNEQLTLHDERFE

check_seq_df(df.head(),'site_seq')

0    _MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTR
1    QKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPG
2    EDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKTHRAIADHLF
3    EDCMSVPGKTHRAIADHLFWsEETKSRFTEYsMTssVMRRN
4    RAIADHLFWsEETKSRFTEYsMTssVMRRNEQLTLHDERFE
Name: site_seq, dtype: object

source

validate_site

 validate_site (site_info, seq)

Validate site position residue match with site residue.

site='S610'
seq = 'MSVPSSLSQSAINANSHGGPALSLPLPLHAAHNQLLNAKLQATAVGPKDLRSAMGEGGGPEPGPANAKWLKEGQNQLRRAATAHRDQNRNVTLTLAEEASQEPEMAPLGPKGLIHLYSELELSAHNAANRGLRGPGLIISTQEQGPDEGEEKAAGEAEEEEEDDDDEEEEEDLSSPPGLPEPLESVEAPPRPQALTDGPREHSKSASLLFGMRNSAASDEDSSWATLSQGSPSYGSPEDTDSFWNPNAFETDSDLPAGWMRVQDTSGTYYWHIPTGTTQWEPPGRASPSQGSSPQEESQLTWTGFAHGEGFEDGEFWKDEPSDEAPMELGLKEPEEGTLTFPAQSLSPEPLPQEEEKLPPRNTNPGIKCFAVRSLGWVEMTEEELAPGRSSVAVNNCIRQLSYHKNNLHDPMSGGWGEGKDLLLQLEDETLKLVEPQSQALLHAQPIISIRVWGVGRDSGRERDFAYVARDKLTQMLKCHVFRCEAPAKNIATSLHEICSKIMAERRNARCLVNGLSLDHSKLVDVPFQVEFPAPKNELVQKFQVYYLGNVPVAKPVGVDVINGALESVLSSSSREQWTPSHVSVAPATLTILHQQTEAVLGECRVRFLSFLAVGRDVHTFAFIMAAGPASFCCHMFWCEPNAASLSEAVQAACMLRYQKCLDARSQASTSCLPAPPAESVARRVGWTVRRGVQSLWGSLKPKRLGAHTP'

validate_site(site,seq)

source

validate_site_df

 validate_site_df (df, site_info_col, protein_seq_col)

Validate site position residue match with site residue in a dataframe.

validate_site_df(df.head(),'site','substrate_sequence')

0    1
1    1
2    1
3    1
4    1
dtype: int64

Phosphorylate protein seq

source

phosphorylate_seq

 phosphorylate_seq (seq, *sites)

Phosphorylate protein sequence based on phosphosites (e.g.,S140).

	Type	Details
seq		full protein sequence
sites	VAR_POSITIONAL	site info, e.g., S140

seq = 'MSKSESPKEPEQLRKLFIGGLSFETTDESLRSHFEQWGTLTDCVVMRDPNTKRSRGFGFVTYATVEEVDAAMNARPHKVDGRVVEPKRAVSREDSQRPDAHLTVKKIFVGGIKEDTEEHHLRDYFEQYGKIEVIEIMTDRGSGKKRGFAFVTFDDHDSVDKIVIQKYHTVNGHNCEVRKALSKQEMASASSSQRGRSGSGNFGGGRGGGFGGNDNFGRGGNFSGRGGFGGSRGGGGYGGSGDGYNGFGNDGSNFGGGGSYNDFGNYNNQSSNFGPMKGGNFEGRSSGPHGGGGQYFAKPRNQGGYGGSSSSSSYGSGRRF'
phosphorylate_seq(seq,*['S95', 'S22', 'T25', 'S6', 'S158'])

'MSKSEsPKEPEQLRKLFIGGLsFEtTDESLRSHFEQWGTLTDCVVMRDPNTKRSRGFGFVTYATVEEVDAAMNARPHKVDGRVVEPKRAVSREDsQRPDAHLTVKKIFVGGIKEDTEEHHLRDYFEQYGKIEVIEIMTDRGSGKKRGFAFVTFDDHDsVDKIVIQKYHTVNGHNCEVRKALSKQEMASASSSQRGRSGSGNFGGGRGGGFGGNDNFGRGGNFSGRGGFGGSRGGGGYGGSGDGYNGFGNDGSNFGGGGSYNDFGNYNNQSSNFGPMKGGNFEGRSSGPHGGGGQYFAKPRNQGGYGGSSSSSSYGSGRRF'

source

phosphorylate_seq_df

 phosphorylate_seq_df (df, id_col='substrate_uniprot',
                       seq_col='substrate_sequence', site_col='site')

Phosphorylate whole sequence based on phosphosites in a dataframe

	Type	Default	Details
df
id_col	str	substrate_uniprot	column of sequence ID
seq_col	str	substrate_sequence	column that contains protein sequence
site_col	str	site	column that contains site info, e.g., S140

df=Data.get_human_site()
df.head()

	substrate_uniprot	substrate_genes	site	source	AM_pathogenicity	substrate_sequence	substrate_species	sub_site	substrate_phosphoseq	position	site_seq
0	A0A024R4G9	C19orf48 MGC13170 hCG_2008493	S20	psp	NaN	MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSH...	Homo sapiens (Human)	A0A024R4G9_S20	MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTRTWLLSH...	20	_MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTR
1	A0A075B6Q4	None	S24	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S24	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	24	QKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPG
2	A0A075B6Q4	None	S35	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S35	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	35	EDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKTHRAIADHLF
3	A0A075B6Q4	None	S57	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S57	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	57	EDCMSVPGKTHRAIADHLFWsEETKSRFTEYsMTssVMRRN
4	A0A075B6Q4	None	S68	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S68	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	68	RAIADHLFWsEETKSRFTEYsMTssVMRRNEQLTLHDERFE

phosphorylate_seq_df(df.head(100),'substrate_uniprot','substrate_sequence','site')

	substrate_uniprot	site	substrate_sequence	phosphoseq
0	A0A024R4G9	[S20]	MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSH...	MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTRTWLLSH...
1	A0A075B6Q4	[S24, S35, S57, S68, S71, S72]	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...
...	...	...	...	...
22	A0A0A6YYL6	[S5, Y139, S141, S142]	MVRYSLDPENPTKSCKSRGSNLRVHFKNTRETAQAIKGMHIRKATK...	MVRYsLDPENPTKSCKSRGSNLRVHFKNTRETAQAIKGMHIRKATK...
23	A0A0B4J1R7	[T6, S43, S45, S46]	MMATGTPESQARFGQSVKGLLTEKVTTCGTDVIALTKQVLKGSRSS...	MMATGtPESQARFGQSVKGLLTEKVTTCGTDVIALTKQVLKGsRss...

24 rows × 4 columns

Extract site seq

source

extract_site_seq

 extract_site_seq (df:pandas.core.frame.DataFrame, seq_col:str,
                   site_col:str, n=7)

Extract -n to +n site sequence from protein sequence

	Type	Default	Details
df	DataFrame		dataframe that contains protein sequence
seq_col	str		column name of protein sequence
site_col	str		column name of site information (e.g., S10)
n	int	7	length of surrounding sequence (default -7 to +7)

As some datasets only contains protein information and position of phosphorylation sites, but not phosphorylation site sequence, we can retreive protein sequence and use this function to get -7 to +7 phosphorylation site sequence (as numpy array).

Remember to validate the phospho-acceptor at position 0 before extract the site sequence, as there could be mismatch due to the protein sequence database updates.

df.head()

	substrate_uniprot	substrate_genes	site	source	AM_pathogenicity	substrate_sequence	substrate_species	sub_site	substrate_phosphoseq	position	site_seq
0	A0A024R4G9	C19orf48 MGC13170 hCG_2008493	S20	psp	NaN	MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSH...	Homo sapiens (Human)	A0A024R4G9_S20	MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTRTWLLSH...	20	_MTVLEAVLEIQAITGSRLLsMVPGPARPPGSCWDPTQCTR
1	A0A075B6Q4	None	S24	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S24	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	24	QKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPG
2	A0A075B6Q4	None	S35	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S35	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	35	EDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKTHRAIADHLF
3	A0A075B6Q4	None	S57	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S57	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	57	EDCMSVPGKTHRAIADHLFWsEETKSRFTEYsMTssVMRRN
4	A0A075B6Q4	None	S68	ochoa	NaN	MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKT...	Homo sapiens (Human)	A0A075B6Q4_S68	MDIQKSENEDDSEWEDVDDEKGDsNDDYDSAGLLsDEDCMSVPGKT...	68	RAIADHLFWsEETKSRFTEYsMTssVMRRNEQLTLHDERFE

extract_site_seq(df.head(),
                 seq_col='substrate_sequence',
                 site_col='site',
                 n=30
                 )

100%|██████████| 5/5 [00:00<00:00, 4705.30it/s]

array(['___________MTVLEAVLEIQAITGSRLLSMVPGPARPPGSCWDPTQCTRTWLLSHTPRR',
       '_______MDIQKSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKTHRAIADHL',
       'KSENEDDSEWEDVDDEKGDSNDDYDSAGLLSDEDCMSVPGKTHRAIADHLFWSEETKSRFT',
       'DYDSAGLLSDEDCMSVPGKTHRAIADHLFWSEETKSRFTEYSMTSSVMRRNEQLTLHDERF',
       'DCMSVPGKTHRAIADHLFWSEETKSRFTEYSMTSSVMRRNEQLTLHDERFEKFYEQYDDDE'],
      dtype='<U61')

Reactome pathway

source

get_reactome_raw

 get_reactome_raw (gene_list)

Reactome pathway analysis for a given gene set; returns raw output in dataframe.

pi3ks=['PIK3CA','PIK3CB','PIK3CD','PIK3CG','PIK3R1','PIK3R2','PIK3R3','PTEN','AKT1','AKT2','AKT3','MTOR','RICTOR','RPTOR','TSC1','TSC2','PDK1','IRS1','IRS2','INSR','IGF1R','GAB1','HRAS','NRAS','KRAS','EGFR','ERBB2','ERBB3','ERBB4']

raw_out = get_reactome_raw(pi3ks)
raw_out.head()

	stId	dbId	name	llp	inDisease	species.dbId	species.taxId	species.name	entities.resource	entities.total	entities.found	entities.ratio	entities.pValue	entities.fdr	entities.exp	reactions.resource	reactions.total	reactions.found	reactions.ratio
0	R-HSA-1963640	1963640	GRB2 events in ERBB2 signaling	True	False	48887	9606	Homo sapiens	TOTAL	21	9	0.001327	1.110223e-16	1.110223e-15	[]	TOTAL	4	4	0.000261
1	R-HSA-9665348	9665348	Signaling by ERBB2 ECD mutants	True	True	48887	9606	Homo sapiens	TOTAL	23	9	0.001453	1.110223e-16	1.110223e-15	[]	TOTAL	15	15	0.000978
2	R-HSA-9664565	9664565	Signaling by ERBB2 KD Mutants	True	True	48887	9606	Homo sapiens	TOTAL	35	13	0.002212	1.110223e-16	1.110223e-15	[]	TOTAL	17	17	0.001108
3	R-HSA-1227990	1227990	Signaling by ERBB2 in Cancer	False	True	48887	9606	Homo sapiens	TOTAL	36	13	0.002275	1.110223e-16	1.110223e-15	[]	TOTAL	62	62	0.004041
4	R-HSA-9665686	9665686	Signaling by ERBB2 TMD/JMD mutants	True	True	48887	9606	Homo sapiens	TOTAL	30	10	0.001896	1.110223e-16	1.110223e-15	[]	TOTAL	13	13	0.000847

source

get_reactome

 get_reactome (gene_list)

Reactome pathway analysis for a given gene set; returns formated output in dataframe with additional -log10(p)

format_out = get_reactome(pi3ks)
format_out.head()

	name	pValue	-log10_pValue
0	GRB2 events in ERBB2 signaling	1.110223e-16	15.955
1	Signaling by ERBB2 ECD mutants	1.110223e-16	15.955
2	Signaling by ERBB2 KD Mutants	1.110223e-16	15.955
3	Signaling by ERBB2 in Cancer	1.110223e-16	15.955
4	Signaling by ERBB2 TMD/JMD mutants	1.110223e-16	15.955

format_out

	name	pValue	-log10_pValue
0	GRB2 events in ERBB2 signaling	1.110223e-16	15.955
1	Signaling by ERBB2 ECD mutants	1.110223e-16	15.955
2	Signaling by ERBB2 KD Mutants	1.110223e-16	15.955
3	Signaling by ERBB2 in Cancer	1.110223e-16	15.955
4	Signaling by ERBB2 TMD/JMD mutants	1.110223e-16	15.955
...	...	...	...
391	Metabolism of vitamins and cofactors	6.436050e-01	0.191
392	Neutrophil degranulation	7.242278e-01	0.140
393	Metabolism of RNA	8.996551e-01	0.046
394	Post-translational protein modification	9.908668e-01	0.004
395	Metabolism of proteins	9.909976e-01	0.004

396 rows × 3 columns

source

plot_path

 plot_path (react_out, top_n=10, max_label_length=80)

Plot the bar graph of pathways from get_reactome function.

plot_path(format_out)
plt.title('PI3K Pathways');

Setup

Commons

save_show

get_path

get_diff

Checker

check_seq

check_seqs

check_seq_df

validate_site

validate_site_df

Phosphorylate protein seq

phosphorylate_seq

phosphorylate_seq_df

Extract site seq

extract_site_seq

Reactome pathway

get_reactome_raw

get_reactome

plot_path

End