Notebook RCM Part 1 PanCan Figure 3

Figure3

Printing out metabolite names and their cluster¶

In [2]:

import pandas as pd
import os


cancer = 'PanCan'
input_dir = 'Input_RCM'
output_dir = 'Output_Data'
supp_dir = 'Required_Refs'
fig_dir = 'Output_Figures'
regLabel = 'RG2_Changes_filtered'

df = pd.read_csv(os.path.join(output_dir, f'sircle_PorMandR_{cancer}.csv'))

# Now just print out the cluster label and then the gene for the different metabolites
metabolites = ['HK1', 'HK2', 'HK3', 'GPI', 'PFK1', 'ALDOA', 
               'ALDOB', 'ALDOC', 'GAPDH', 'PGK1', 'PGM', 'ENO1', 'ENO2', 
               'ENO3', 'PKM', 'LDHA', 'LDHB', 'LDHC', 'LDHD', 'PDHX', 'PDHA1',
               'PDHA2', 'PDHB', 'MDH2', 'CS', 'ACO2', 'IDH2', 'IDH3A', 'IDH3B',
               'IDH3G', 'OGDH', 'GLUD1', 'GLS', 'HMOX1', 'SUCLG2', 'SUCLG1', 
               'SDHD', 'SDHC', 'SDHB', 'SDHA', 'FH', 'CPS1', 'OTC', 'ASS1', 
               'ASL', 'ARG1', 'GPX1', 'GPX2', 'GPX3', 'GPX4', 'GPX5', 'GPX6', 
              'GPX7', 'GPX8', 'CTH', 'CBS', 'SHMT1', 'SHMT2', 'PSPH', 'PSAT1',
              'PHGDH', 'BHMT', 'BHMT2', 'MAT2B', 'MAT2A', 'MAT1A', 'AHCY']

for m in metabolites:
    try:
        g = df[df['gene_name'] == m]['RG2_Changes_filtered'].values[0]
        print(m, g)
    except:
        print(m)

/var/folders/gq/6ljhmvm1713fykdjqbl188pm0000gn/T/ipykernel_22321/1409286533.py:12: DtypeWarning: Columns (1,2,1161,1163,1164,1167,1176,1177,1178,1179,1180,1181,1182,1195,1197,1198,1202,1203,1208,1974,1975,1976) have mixed types. Specify dtype option on import or set low_memory=False.
  df = pd.read_csv(os.path.join(output_dir, f'sircle_PorMandR_{cancer}.csv'))

HK1 nan
HK2 MDE
HK3 nan
GPI nan
PFK1
ALDOA nan
ALDOB TPDS_TMDE
ALDOC nan
GAPDH MDE_TMDS
PGK1 nan
PGM
ENO1 nan
ENO2 TPDE_TMDS
ENO3 nan
PKM nan
LDHA MDE_TMDS
LDHB nan
LDHC Not-Background
LDHD TMDS
PDHX nan
PDHA1 nan
PDHA2 Not-Background
PDHB nan
MDH2 nan
CS nan
ACO2 nan
IDH2 nan
IDH3A nan
IDH3B nan
IDH3G nan
OGDH nan
GLUD1 nan
GLS nan
HMOX1 nan
SUCLG2 nan
SUCLG1 nan
SDHD nan
SDHC nan
SDHB nan
SDHA nan
FH nan
CPS1 nan
OTC Not-Background
ASS1 nan
ASL nan
ARG1 TPDS_TMDE
GPX1 nan
GPX2 MDE_TMDS
GPX3 MDS
GPX4 nan
GPX5 Not-Background
GPX6 Not-Background
GPX7 TMDE
GPX8 TMDE
CTH nan
CBS Not-Background
SHMT1 nan
SHMT2 nan
PSPH nan
PSAT1 TPDE_TMDS
PHGDH nan
BHMT nan
BHMT2 Not-Background
MAT2B nan
MAT2A nan
MAT1A nan
AHCY nan

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