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Describe the bug
How to handle big dataset? It is suggested to feed pySCENIC raw counts. I have a dataset of the shape(19386, 20483). It stops when running grnboost2().
Steps to reproduce the behavior
Command run when the error occurred:
tf_names = load_tf_names(MM_TFS_FNAME)
# the ranking databases are loaded:
db_fnames = glob.glob(DATABASES_GLOB)
def name(fname):
return os.path.splitext(os.path.basename(fname))[0]
dbs = [RankingDatabase(fname=fname, name=name(fname)) for fname in db_fnames]
dbs
## load the scRNA-seq raw counts to be anbalyzed
RESOURCES_FOLDER="/project/xyang2/heart_dev/IbarraSoria2018_MouseE8.25/"
SC_EXP_FNAME = os.path.join(RESOURCES_FOLDER, "rawcounts_filtered_wSymbols.tsv") # raw counts, mm10
genome = 'mm10'
ex_matrix = pd.read_csv(SC_EXP_FNAME, sep='\t', header=0, index_col=0).T
ex_matrix.shape
# (19386, 20483) # cells , genes
# The arboreto package is used for this phase of the pipeline.
adjacencies = grnboost2(ex_matrix, tf_names=tf_names, verbose=True)
Describe the bug
How to handle big dataset? It is suggested to feed pySCENIC raw counts. I have a dataset of the shape(19386, 20483). It stops when running grnboost2().
Steps to reproduce the behavior
Expected behavior
This is codes following the tutorial at https://pyscenic.readthedocs.io/en/latest/tutorial.html#
Please complete the following information:
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