load_tf_names command not working

[Seandelao]

Hello,

I am trying to utilize Arboreto, but am having difficulty. I am running the following code in Jupiter Notebook:

import os
import pandas as pd

from arboreto.algo import grnboost2, genie3
from arboreto.utils import load_tf_names

if name == 'main':
ex_matrix = pd.read_csv('myDir/1.1_exprMatrix_filtered_t.txt', sep='\t')

tf_names = load_tf_names('myDir//1.1_inputTFs.txt')

network = grnboost2(expression_data=ex_matrix,
                tf_names=tf_names)

network.to_csv('myDir/sc_01_network.tsv', sep='\t', header=False, index=False)

but get an error:

----> 7 tf_names=tf_names)
...
AttributeError: 'DataFrame' object has no attribute 'as_matrix'

Is this an incompatibility with the new pandas version? I am using the following:

Pandas version: 1.0.0
arboreto version: 0.1.5

Thank you!

[jpromeror]

Hello @Seandelao

I had the same issue when running the grnboost2 function. Im guessing that it is a problem with versions and deprecated functions.

I was able to get the function running with the following code:

import os
import glob
import pickle
import pandas as pd
import numpy as np

from dask.diagnostics import ProgressBar

from arboreto.utils import load_tf_names
from arboreto.algo import grnboost2

from pyscenic.rnkdb import FeatherRankingDatabase as RankingDatabase
from pyscenic.utils import modules_from_adjacencies, load_motifs
from pyscenic.prune import prune2df, df2regulons
from pyscenic.aucell import aucell
from pyscenic.binarization import binarize
from pyscenic.cli.utils import save_enriched_motifs

import seaborn as sns

# Define some variables
DATA_FOLDER="/home/jpromero/Data/SCENIC/"
SC_EXP_FNAME = os.path.join(DATA_FOLDER, "Exp_mat.csv")

# Load the expression matrix

ex_matrix = pd.read_csv(SC_EXP_FNAME ,index_col=0)
ex_matrix.head()
ex_matrix.shape

#  list of Transcription Factors(TF) 
tf_names = load_tf_names(MM_TFS_FNAME)
tf_names[:5]

# Transfrom Pandas DataFrame into Numpy array 
ExpMat=ex_matrix.values

# Get gene names 
Genes=ex_matrix.columns.values

# Run grnboost2
adjacencies = grnboost2(ExpMat,gene_names=Genes, tf_names=tf_names, verbose=True)

Hope this helps!

Juan Pablo