Since the original 128-assay dataset is left intact, removing comparison...

You must select either -d pcba_146, -d pcba_2475 or -g GENE_SYMBOL.

At the end you will have a pcba_128.csv.gz, etc file in your DEEPCHEM_DATA_DIR ready for benchmarking

At the end you will have a file, e.g. pcba_146.csv.gz, etc file in your DEEPCHEM_DATA_DIR ready for benchmarking

Also, please note that the pcba_146 corresponds to the following query on PubChem Bioassay Search:

import gzip

import deepchem

import os

import pandas as pd

###

# This script prepares two reference assay datasets for further inspection (e.g., with diff)

###

data_dir = deepchem.utils.get_data_dir()

f_orig = gzip.open(os.path.join(data_dir, "orig/pcba_128.csv.gz"))

f_new = gzip.open(os.path.join(data_dir, "new/pcba_128.csv.gz"))

df_orig = pd.read_csv(f_orig)

df_orig = df_orig.sort_values("mol_id")

df_new = pd.read_csv(f_new)

df_orig = df_orig.fillna(0)

df_new = df_new.fillna(0)

print("{} molecules in original dataset".format(len(df_orig["mol_id"].values)))

print("{} molecules in new dataset: ".format(len(df_new["mol_id"].values)))

set_diff_orig_new = set(df_orig["mol_id"].values).difference(

    set(df_new["mol_id"].values))

set_diff_new_orig = set(df_new["mol_id"].values).difference(

    set(df_orig["mol_id"].values))

print("{} molecules in original dataset but not in new: ".format(

    len(set_diff_orig_new)))

print("{} molecules in new dataset but not in old: ".format(

    len(set_diff_new_orig)))

# Compare all assay results for their intersection

intersection_keys = list(

    set(df_orig["mol_id"]).intersection(set(df_new["mol_id"])))

print("{} molecules in new dataset and in old: ".format(len(intersection_keys)))

print("{}, fraction of molecules in the new dataset and also in old".format(

    len(intersection_keys) / len(df_new)))

df_new = df_new[df_new["mol_id"].isin(intersection_keys)]

df_orig = df_orig[df_orig["mol_id"].isin(intersection_keys)]

print(len(df_new) == len(df_orig))

if (len(df_new) != len(df_orig)):

  raise Exception

df_orig_compare = df_orig.sort_values("mol_id")

df_new_compare = df_new.sort_values("mol_id")

df_new_compare = df_new_compare[df_orig_compare.columns]

# Drop smiles for compare

df_orig_compare = df_orig_compare.drop("smiles", axis=1)

df_new_compare = df_new_compare.drop("smiles", axis=1)

df_orig_compare = df_orig_compare.set_index("mol_id")

df_new_compare = df_new_compare.set_index("mol_id")

df_orig_compare = df_orig_compare.sort_index()

df_new_compare = df_new_compare.sort_index()

df_new_compare.to_csv("new.csv")

df_orig_compare.to_csv("orig.csv")

f_orig.close()

f_new.close()