diff --git a/bin/demuxem.py b/bin/demuxem.py
index 3924f04..f3e69ef 100755
--- a/bin/demuxem.py
+++ b/bin/demuxem.py
@@ -31,16 +31,8 @@
 if __name__ == '__main__':
     output_name = args.outputdir + "/" + args.objectOutDemuxem
     # load input rna data
-    #data = io.read_input(args.rna_matrix_dir, modality="rna")
     rna_data = sc.read_10x_mtx(args.rna_matrix_dir)
     hashing_data = sc.read_10x_mtx(args.hto_matrix_dir,gex_only=False)
-    #data.subset_data(modality_subset=['rna'])
-    #data.concat_data() # in case of multi-organism mixing data
-    # load input hashing data
-    #data.update(io.read_input(args.hto_matrix_dir, modality="hashing"))
-    # Extract rna and hashing data
-    #rna_data = data.get_data(modality="rna")
-    #hashing_data = data.get_data(modality="hashing")
     filter = ""
     if args.filter_demuxem.lower() in ['true', 't', 'yes', 'y', '1']:
         filter = True
@@ -96,7 +88,7 @@
     pg.write_output(mudata, output_name + ".out.demuxEM.zarr.zip")
     print("\nSummary statistics:")
     print("total\t{}".format(rna_data.shape[0]))
-    for name, value in rna_data.obs["demux_type"].value_counts().iteritems():
+    for name, value in rna_data.obs["demux_type"].value_counts().items():
         print("{}\t{}".format(name, value))
     summary = rna_data.obs["demux_type"].value_counts().rename_axis('classification').reset_index(name='counts')
     total = ["total", rna_data.shape[0]]
diff --git a/bin/generate_data.py b/bin/generate_data.py
index 96fc494..7139cd3 100755
--- a/bin/generate_data.py
+++ b/bin/generate_data.py
@@ -3,7 +3,6 @@
 import os
 import scanpy as sc
 import argparse
-import muon as mu
 
 parser = argparse.ArgumentParser(description="Parameters for generating anndata and mudata")
 parser.add_argument("--assignment", help="Folder which contains cSV file with demultiplexing assignment", default=None)
diff --git a/bin/summary_gene.py b/bin/summary_gene.py
index 3564494..7e50812 100755
--- a/bin/summary_gene.py
+++ b/bin/summary_gene.py
@@ -1,9 +1,11 @@
 #!/usr/bin/env python
-import pandas as pd
 import os
-import scanpy as sc
 import argparse
-import muon as mu
+import numpy as np
+import scanpy as sc
+import pandas as pd
+from mudata import MuData
+
 
 parser = argparse.ArgumentParser(description="Parameters for summary process")
 parser.add_argument("--demuxlet", help="Folder containing output files of Demuxlet", default=None)
@@ -15,7 +17,6 @@
 parser.add_argument("--generate_mudata", help="Generate mudata", action='store_true')
 parser.add_argument("--read_rna_mtx", help="10x-Genomics-formatted mtx directory for gene expression", default=None)
 parser.add_argument("--read_hto_mtx", help="10x-Genomics-formatted mtx directory for HTO expression", default=None)
-#parser.add_argument("--sampleId", help="sampleID if multiple samples are demultiplexed", default=None)
 
 args = parser.parse_args()
 
@@ -26,14 +27,12 @@ def demuxlet_summary(demuxlet_res, raw_adata, raw_mudata):
         obs_res_dir = [file for file in os.listdir(x) if file.endswith('.best')][0]
         obs_res = pd.read_csv(os.path.join(x, obs_res_dir), sep='\t')
         obs_res = obs_res.iloc[:, [1, 4, 5]]
-        obs_res['Assignment'] = obs_res['BEST.GUESS'].apply(lambda x: x.split(',')[1] if x.split(',')[0] == x.split(',')[1] else "NA")
-        obs_res.loc[obs_res['Assignment'] == "NA", 'Assignment'] = "doublet"
-        obs_res.loc[obs_res['DROPLET.TYPE'] == "AMB", 'Assignment'] = "negative"
-        obs_res.rename(columns={'BARCODE': 'Barcode'}, inplace=True)
-        demuxlet_assign = obs_res[['Barcode', 'Assignment']]
-        demuxlet_assign.index = demuxlet_assign.Barcode
-        demuxlet_assign = demuxlet_assign.drop(columns=['Barcode'])
-        demuxlet_assign.rename(columns={'Assignment': os.path.basename(x)}, inplace=True)
+        obs_res['Assignment'] = np.where(obs_res['BEST.GUESS'].str.split(',').str[0] == obs_res['BEST.GUESS'].str.split(',').str[1], 
+                                         obs_res['BEST.GUESS'].str.split(',').str[0], "doublet")
+        obs_res['Assignment'] = np.where(obs_res['DROPLET.TYPE'] == 'AMB', 'negative', obs_res['Assignment'])
+        obs_res.rename(columns={"BARCODE": "Barcode", "Assignment": os.path.basename(x)}, inplace=True)
+        obs_res.set_index('Barcode', inplace=True)
+        demuxlet_assign = obs_res[[os.path.basename(x)]]
         
         if raw_adata is not None:
             adata = raw_adata.copy()
@@ -53,7 +52,7 @@ def demuxlet_summary(demuxlet_res, raw_adata, raw_mudata):
     assign.to_csv("genetic_summary/demuxlet_assignment.csv", quoting=False)
 
     classi = assign.copy()
-    classi[(classi != "negative") & (classi != "doublet")] = "singlet"
+    classi[~classi.isin(["doublet", "negative"])] = "singlet"
     classi.to_csv("genetic_summary/demuxlet_classification.csv", quoting=False)
 
     params = pd.concat(params, axis=1)
@@ -67,14 +66,12 @@ def freemuxlet_summary(freemuxlet_res, raw_adata, raw_mudata):
         obs_res_dir = [file for file in os.listdir(x) if file.endswith('.clust1.samples.gz')][0]
         obs_res = pd.read_csv(os.path.join(x, obs_res_dir), sep='\t')
         obs_res = obs_res.iloc[:, [1, 4, 5]]
-        obs_res['Assignment'] = obs_res['BEST.GUESS'].apply(lambda x: x.split(',')[1] if x.split(',')[0] == x.split(',')[1] else "NA")
-        obs_res.loc[obs_res['Assignment'] == "NA", 'Assignment'] = "doublet"
-        obs_res.loc[obs_res['DROPLET.TYPE'] == "AMB", 'Assignment'] = "negative"
-        obs_res.rename(columns={'BARCODE': 'Barcode'}, inplace=True)
-        freemuxlet_assign = obs_res[['Barcode', 'Assignment']]
-        freemuxlet_assign.index = freemuxlet_assign.Barcode
-        freemuxlet_assign = freemuxlet_assign.drop(columns=['Barcode'])
-        freemuxlet_assign.rename(columns={'Assignment': os.path.basename(x)}, inplace=True)
+        obs_res['Assignment'] = np.where(obs_res['BEST.GUESS'].str.split(',').str[0] == obs_res['BEST.GUESS'].str.split(',').str[1], 
+                                                obs_res['BEST.GUESS'].str.split(',').str[0], "doublet")
+        obs_res['Assignment'] = np.where(obs_res['DROPLET.TYPE'] == 'AMB', 'negative', obs_res['Assignment'])
+        obs_res.rename(columns={"BARCODE": "Barcode", "Assignment": os.path.basename(x)}, inplace=True)
+        obs_res.set_index('Barcode', inplace=True)
+        freemuxlet_assign = obs_res[[os.path.basename(x)]]
         
         if raw_adata is not None:
             adata = raw_adata.copy()
@@ -94,7 +91,7 @@ def freemuxlet_summary(freemuxlet_res, raw_adata, raw_mudata):
     assign.to_csv("genetic_summary/freemuxlet_assignment.csv", quoting=False)
 
     classi = assign.copy()
-    classi[(classi != "negative") & (classi != "doublet")] = "singlet"
+    classi[~classi.isin(["doublet", "negative"])] = "singlet"
     classi.to_csv("genetic_summary/freemuxlet_classification.csv", quoting=False)
 
     params = pd.concat(params, axis=1)
@@ -112,11 +109,9 @@ def souporcell_summary(souporcell_res, raw_adata, raw_mudata):
         obs_res = obs_res.iloc[:, 0:3]
         obs_res.loc[obs_res['status'] == 'doublet', 'assignment'] = 'doublet'
         obs_res.loc[obs_res['status'] == 'unassigned', 'assignment'] = 'negative'
-        obs_res = obs_res.drop('status', axis=1)
-        obs_res.rename(columns={'barcode': 'Barcode'}, inplace=True)
-        obs_res.index = obs_res.Barcode
-        obs_res = obs_res.drop(columns=['Barcode'])
-        obs_res.columns = [os.path.basename(x)]
+        obs_res.rename(columns={'barcode': 'Barcode', 'assignment': os.path.basename(x)}, inplace=True)
+        obs_res.set_index('Barcode', inplace=True)
+        obs_res = obs_res[[os.path.basename(x)]]
 
         if raw_adata is not None:
             adata = raw_adata.copy()
@@ -136,7 +131,7 @@ def souporcell_summary(souporcell_res, raw_adata, raw_mudata):
     assign.to_csv("genetic_summary/souporcell_assignment.csv", quoting=False)
 
     classi = assign.copy()
-    classi[(classi != "negative") & (classi != "doublet")] = "singlet"
+    classi[~classi.isin(["doublet", "negative"])] = "singlet"
     classi.to_csv("genetic_summary/souporcell_classification.csv", quoting=False)
 
     params = pd.concat(params, axis=1)
@@ -152,12 +147,11 @@ def vireo_summary(vireo_res, raw_adata, raw_mudata):
             if "donor_ids.tsv" in files:
                 obs_res_dir = os.path.join(root, "donor_ids.tsv")
         obs_res = pd.read_csv(os.path.join(x, obs_res_dir), sep='\t')
-        obs_res = obs_res.iloc[:, [0, 1]]
+        bs_res = obs_res.iloc[:, [0, 1]]
         obs_res[obs_res == "unassigned"] = "negative"
-        obs_res.rename(columns={'cell': 'Barcode'}, inplace=True)
-        obs_res.index = obs_res.Barcode
-        obs_res = obs_res.drop(columns=['Barcode'])
-        obs_res.columns = [os.path.basename(x)]
+        obs_res.rename(columns={'cell': 'Barcode', 'donor_id': os.path.basename(x)}, inplace=True)
+        obs_res.set_index('Barcode', inplace=True)
+        obs_res = obs_res[[os.path.basename(x)]]
 
         if raw_adata is not None:
             adata = raw_adata.copy()
@@ -177,7 +171,7 @@ def vireo_summary(vireo_res, raw_adata, raw_mudata):
     assign.to_csv("genetic_summary/vireo_assignment.csv", quoting=False)
 
     classi = assign.copy()
-    classi[(classi != "negative") & (classi != "doublet")] = "singlet"
+    classi[~classi.isin(["doublet", "negative"])] = "singlet"
     classi.to_csv("genetic_summary/vireo_classification.csv", quoting=False)
 
     params = pd.concat(params, axis=1)
@@ -188,17 +182,13 @@ def scsplit_summary(scsplit_res, raw_adata, raw_mudata):
     params = []
 
     for x in scsplit_res:
-        obs_res_dir = ""
-        for root, dirs, files in os.walk(x):
-            if "scSplit_result.csv" in files:
-                obs_res_dir = os.path.join(root, "scSplit_result.csv")
+        obs_res_dir = next((os.path.join(root, "scSplit_result.csv") for root, dirs, files in os.walk(x) if "scSplit_result.csv" in files),"")
         obs_res = pd.read_table(obs_res_dir)
         obs_res['Assignment'] = obs_res['Cluster'].str.split('-').str[1]
         obs_res['Classification'] = obs_res['Cluster'].str.split('-').str[0]
-        obs_res = obs_res.drop('Cluster', axis=1)
         obs_res.loc[obs_res['Classification'] == 'DBL', 'Assignment'] = 'doublet'        
-        obs_res.index = obs_res.Barcode
-        obs_res = obs_res.drop(columns=['Barcode', 'Classification'])
+        obs_res = obs_res.drop(columns=['Cluster', 'Classification'])
+        obs_res.set_index('Barcode', inplace=True)
         obs_res.columns = [os.path.basename(x)]
         
         if raw_adata is not None:
@@ -236,9 +226,11 @@ def scsplit_summary(scsplit_res, raw_adata, raw_mudata):
         adata = sc.read_10x_mtx(args.read_rna_mtx)
 
     if args.generate_mudata is True:
-        # TODO
-        os.mkdir("genetic_summary/mudata")
-        pass
+        if not os.path.exists("genetic_summary/mudata"):
+            os.mkdir("genetic_summary/mudata")
+        rna_data = sc.read_10x_mtx(args.read_rna_mtx)
+        hto_data = sc.read_10x_mtx(args.read_hto_mtx, gex_only=False)
+        mudata = MuData({"rna": rna_data, "hto": hto_data })
 
     if args.demuxlet is not None:
         demuxlet_res = args.demuxlet.split(':')
diff --git a/bin/summary_hash.py b/bin/summary_hash.py
index f43603a..11d1e91 100755
--- a/bin/summary_hash.py
+++ b/bin/summary_hash.py
@@ -19,7 +19,6 @@
 parser.add_argument("--generate_mudata", help="Generate mudata", action='store_true')
 parser.add_argument("--read_rna_mtx", help="10x-Genomics-formatted mtx directory for gene expression", default=None)
 parser.add_argument("--read_hto_mtx", help="10x-Genomics-formatted mtx directory for HTO expression", default=None)
-parser.add_argument("--sampleId", help="sampleID if multiple samples are demultiplexed", default=None)
 
 args = parser.parse_args()
 
@@ -30,13 +29,10 @@ def demuxem_summary(demuxem_res, raw_adata, raw_mudata):
     for x in demuxem_res:
         obs_res_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("_obs.csv")][0])
         obs_res = pd.read_csv(obs_res_dir)
-        obs_res.rename(columns={obs_res.columns[0]: "Barcode"}, inplace=True)
-        demuxem_assign = obs_res[["Barcode", "assignment"]]
-        demuxem_assign.columns = ["Barcode", os.path.basename(x)]
-        demuxem_assign.loc[:, "Barcode"] = demuxem_assign["Barcode"].apply(lambda x: x + "-1")
-        #demuxem_assign["Barcode"] = demuxem_assign["Barcode"].astype(str) + "-1"
-        demuxem_assign.index = demuxem_assign.Barcode
-        demuxem_assign = demuxem_assign.drop(columns=['Barcode'])
+        obs_res.loc[:, "barcodekey"] = obs_res["barcodekey"].apply(lambda x: x + "-1")
+        demuxem_assign = obs_res[["barcodekey", "assignment"]]
+        demuxem_assign.columns = ["Barcode",os.path.basename(x)]
+        demuxem_assign.set_index("Barcode", inplace=True)
         assign.append(demuxem_assign)
         
         if raw_adata is not None:
@@ -56,21 +52,17 @@ def demuxem_summary(demuxem_res, raw_adata, raw_mudata):
             mudata.update()
             mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
-        demuxem_classi = obs_res[["Barcode", "demux_type"]]
+        demuxem_classi = obs_res[["barcodekey", "demux_type"]]
         demuxem_classi.columns = ["Barcode", os.path.basename(x)]
         demuxem_classi = demuxem_classi.replace("unknown", "negative")
-        demuxem_classi.loc[:, "Barcode"] = demuxem_classi["Barcode"].apply(lambda x: x + '-1')
-        demuxem_classi.index = demuxem_classi.Barcode
-        demuxem_classi = demuxem_classi.drop(columns=['Barcode'])
+        demuxem_classi.set_index("Barcode", inplace=True)
         classi.append(demuxem_classi)
 
         params_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("params.csv")][0])
         params_res = pd.read_csv(params_dir, keep_default_na=False, index_col=0)
-        #params_res.rename(columns={params_res.columns[1]: os.path.basename(x)}, inplace=True)
         params_res.columns = [os.path.basename(x)]
         params.append(params_res)
         
-
     assign = pd.concat(assign, axis=1)
     assign.to_csv("hash_summary/demuxem_assignment.csv", quoting=False)
 
@@ -113,13 +105,9 @@ def hashsolo_summary(hashsolo_res, raw_adata, raw_mudata):
             mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
         hashsolo_classi = obs_res[["most_likely_hypothesis"]]
-        hashsolo_classi_copy = hashsolo_classi.copy()
-        hashsolo_classi_copy.loc[hashsolo_classi_copy["most_likely_hypothesis"] == 0.0 , "most_likely_hypothesis"] = "negative"
-        hashsolo_classi_copy.loc[hashsolo_classi_copy["most_likely_hypothesis"] == 1.0 , "most_likely_hypothesis"] = "singlet"
-        hashsolo_classi_copy.loc[hashsolo_classi_copy["most_likely_hypothesis"] == 2.0 , "most_likely_hypothesis"] = "doublet"
-        
-        hashsolo_classi_copy.columns = [os.path.basename(x)]
-        classi.append(hashsolo_classi_copy)
+        hashsolo_classi.loc[:, "most_likely_hypothesis"] = hashsolo_classi["most_likely_hypothesis"].replace({0.0: "negative", 1.0: "singlet", 2.0: "doublet"})
+        hashsolo_classi.columns = [os.path.basename(x)]
+        classi.append(hashsolo_classi)
     
         params_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("params.csv")][0])
         params_res = pd.read_csv(params_dir, keep_default_na=False, index_col=0)
@@ -170,7 +158,6 @@ def hasheddrops_summary(hasheddrops_res, raw_adata, raw_mudata):
             
             mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
-
         hasheddrops_classi = obs_res[["Barcode", "Classification"]]
         hasheddrops_classi = hasheddrops_classi.rename(columns={"Classification": os.path.basename(x)})
         classi.append(hasheddrops_classi)
@@ -196,10 +183,8 @@ def multiseq_summary(multiseq_res, raw_adata, raw_mudata):
         obs_res_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("_res.csv")][0])
         multiseq_assign = pd.read_csv(obs_res_dir)
         multiseq_assign.columns = ["Barcode", os.path.basename(x)]
-        multiseq_assign.index = multiseq_assign.Barcode
-        multiseq_assign = multiseq_assign.drop(columns=['Barcode'])
-        multiseq_assign.replace("Doublet", "doublet", inplace=True)
-        multiseq_assign.replace("Negative", "negative", inplace=True)
+        multiseq_assign.set_index("Barcode", inplace=True)
+        multiseq_assign.replace({"Doublet": "doublet", "Negative": "negative"}, inplace=True)
         assign.append(multiseq_assign)
         
         if raw_adata is not None:
@@ -219,7 +204,6 @@ def multiseq_summary(multiseq_res, raw_adata, raw_mudata):
             mudata.update()
             mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
-
         params_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("params.csv")][0])
         params_res = pd.read_csv(params_dir, usecols=[1, 2], keep_default_na=False, index_col=0)
         params_res.columns = [os.path.basename(x)]
@@ -229,7 +213,7 @@ def multiseq_summary(multiseq_res, raw_adata, raw_mudata):
     assign.to_csv("hash_summary/multiseq_assignment.csv", quoting=False)
 
     classi = assign.copy()
-    classi[(classi != "doublet") & (classi != "negative")] = "singlet"
+    classi[~classi.isin(["doublet", "negative"])] = "singlet"
     classi.to_csv("hash_summary/multiseq_classification.csv", quoting=False)
 
     params = pd.concat(params, axis=1)
@@ -243,10 +227,8 @@ def htodemux_summary(htodemux_res, raw_adata, raw_mudata):
         obs_res_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("_assignment_htodemux.csv")][0])
         htodemux_assign = pd.read_csv(obs_res_dir)
         htodemux_assign.columns = ["Barcode", os.path.basename(x)]
-        htodemux_assign.replace("Doublet", "doublet", inplace=True)
-        htodemux_assign.replace("Negative", "negative", inplace=True)
-        htodemux_assign.index = htodemux_assign.Barcode
-        htodemux_assign = htodemux_assign.drop(columns=['Barcode'])
+        htodemux_assign.replace({"Doublet": "doublet", "Negative": "negative"}, inplace=True)
+        htodemux_assign.set_index("Barcode", inplace=True)
         assign.append(htodemux_assign)
 
         if raw_adata is not None:
@@ -266,18 +248,13 @@ def htodemux_summary(htodemux_res, raw_adata, raw_mudata):
             mudata.update()
             mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
-
         obs_res_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename.endswith("_classification_htodemux.csv")][0])
         htodemux_classi = pd.read_csv(obs_res_dir)
         htodemux_classi.columns = ["Barcode", os.path.basename(x)]
-        htodemux_classi.replace("Singlet", "singlet", inplace=True)
-        htodemux_classi.replace("Doublet", "doublet", inplace=True)
-        htodemux_classi.replace("Negative", "negative", inplace=True)
-        htodemux_classi.index = htodemux_classi.Barcode
-        htodemux_classi = htodemux_classi.drop(columns=['Barcode'])
+        htodemux_classi.replace({"Doublet": "doublet", "Negative": "negative", "Singlet": "singlet"}, inplace=True)
+        htodemux_classi.set_index("Barcode", inplace=True)
         classi.append(htodemux_classi)
 
-
         params_dir = os.path.join(x, [filename for filename in os.listdir(x) if filename == "params.csv"][0])
         params_res = pd.read_csv(params_dir, usecols=[1, 2], keep_default_na=False, index_col=0)
         params_res.columns = [os.path.basename(x)]
@@ -345,10 +322,10 @@ def demuxmix_summary(demuxmix_res,raw_adata, raw_mudata):
         classi_df.to_csv("hash_summary" + "/demuxmix_classification.csv",index=False)
         
         assign_df = pd.concat(assign, axis=1, join="outer")
-        assign_df.to_csv("hash_summary"  +"/demuxmix_assignment.csv",index=False)
+        assign_df.to_csv("hash_summary" + "/demuxmix_assignment.csv",index=False)
 
         params = pd.concat(params, axis=1)
-        params.to_csv("hash_summary"  +"/demuxmix_params.csv",index=False)
+        params.to_csv("hash_summary" + "/demuxmix_params.csv",index=False)
     else:
         print("No results found for Demuxmix")
 
@@ -473,7 +450,7 @@ def bff_summary(bff_res,raw_adata, raw_mudata):
                 mudata.update()
                 mudata.write("hash_summary/mudata/mudata_with_mudata_"+ os.path.basename(x)+".h5mu") 
 
-                
+
             dt_classi = data_bff.copy()
             column_names_class = ["bff_raw","bff_cluster","consensuscall"]
             for column in column_names_class:
@@ -507,13 +484,14 @@ def bff_summary(bff_res,raw_adata, raw_mudata):
         os.mkdir("hash_summary")
 
     if args.generate_anndata is True:
-        os.mkdir("hash_summary/adata")
+        if not os.path.exists("hash_summary/adata"):
+            os.mkdir("hash_summary/adata")
         adata = sc.read_10x_mtx(args.read_rna_mtx)
 
     if args.generate_mudata is True:
-        os.mkdir("hash_summary/mudata")
+        if not os.path.exists("hash_summary/mudata"):
+            os.mkdir("hash_summary/mudata")
         rna_data = sc.read_10x_mtx(args.read_rna_mtx)
-        path_hto = args.read_hto_mtx
         hto_data = sc.read_10x_mtx(args.read_hto_mtx, gex_only=False)
         mudata = MuData({"rna": rna_data, "hto": hto_data })
         
@@ -549,7 +527,6 @@ def bff_summary(bff_res,raw_adata, raw_mudata):
         bff_res = args.bff.split(':')
         bff_summary(bff_res, adata, mudata)
 
-
     # Read and combine assignment files
     assignment = [file for file in os.listdir("hash_summary") if file.endswith("_assignment.csv")]
     assignment_all = pd.read_csv(os.path.join("hash_summary", assignment[0]))
diff --git a/main.nf b/main.nf
index 897cb4c..547e332 100644
--- a/main.nf
+++ b/main.nf
@@ -9,7 +9,7 @@ process summary_all{
     publishDir "$projectDir/$params.outdir/$params.mode", mode: 'copy'
     label 'small_mem'
 
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         path gene_demulti_result
@@ -26,7 +26,7 @@ process summary_all{
 process generate_data{
     publishDir "$projectDir/$params.outdir/$params.mode/data_output", mode: 'copy'
 
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         path assignment
diff --git a/modules/gene_demultiplexing.nf b/modules/gene_demultiplexing.nf
index e52d19d..dbf5c2a 100644
--- a/modules/gene_demultiplexing.nf
+++ b/modules/gene_demultiplexing.nf
@@ -14,7 +14,7 @@ process summary{
     publishDir "$projectDir/$params.outdir/$sampleId/$params.mode/gene_demulti", mode: 'copy'
     label 'small_mem'
 
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         tuple val(sampleId), path(hto_matrix, stageAs: 'hto_data'), path(rna_matrix, stageAs: 'rna_data')
diff --git a/modules/hash_demulti/demuxem.nf b/modules/hash_demulti/demuxem.nf
index 42e4106..65b5033 100644
--- a/modules/hash_demulti/demuxem.nf
+++ b/modules/hash_demulti/demuxem.nf
@@ -5,7 +5,7 @@ process demuxem{
     publishDir "$projectDir/$params.outdir/$sampleId/$params.mode/hash_demulti/demuxem", mode:'copy'
     label 'small_mem'
 
-    conda "python=3.9 bioconda::pegasuspy pandas<2.0.0 demuxEM"
+    conda "python bioconda::pegasuspy pandas scanpy demuxEM"
     
     input:
         tuple val(sampleId), path(raw_hto_matrix_dir, stageAs: "hto_data_${params.hto_matrix_demuxem}"), 
diff --git a/modules/hash_demultiplexing.nf b/modules/hash_demultiplexing.nf
index 41649ae..9ae2a9e 100644
--- a/modules/hash_demultiplexing.nf
+++ b/modules/hash_demultiplexing.nf
@@ -15,7 +15,7 @@ process summary{
     publishDir "$projectDir/$params.outdir/$sampleId/$params.mode/hash_demulti", mode: 'copy'
     label 'small_mem'
         
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         tuple val(sampleId), path(hto_matrix, stageAs: 'hto_data'), path(rna_matrix, stageAs: 'rna_data')
@@ -94,7 +94,7 @@ process summary{
         }
         
         """
-        summary_hash.py $demuxem_files $htodemux_files $multiseq_files $hashedDrops_files $hashsolo_files $demuxmix_files $gmmDemux_files $bff_files $generate_adata $generate_mdata --sampleId $sampleId
+        summary_hash.py $demuxem_files $htodemux_files $multiseq_files $hashedDrops_files $hashsolo_files $demuxmix_files $gmmDemux_files $bff_files $generate_adata $generate_mdata
         """
 }
 
diff --git a/modules/multi_demultiplexing.nf b/modules/multi_demultiplexing.nf
index 757cf20..cfbeafb 100644
--- a/modules/multi_demultiplexing.nf
+++ b/modules/multi_demultiplexing.nf
@@ -8,7 +8,7 @@ process generate_data{
     publishDir "$projectDir/$params.outdir/$sampleId/$params.mode/data_output", mode: 'copy'
     label 'small_mem'
 
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         tuple val(sampleId), val(hto_matrix), val(rna_matrix), path(assignment)
@@ -48,7 +48,7 @@ process summary_all{
     publishDir "$projectDir/$params.outdir/$sampleId/$params.mode", mode: 'copy'
     label 'small_mem'
     
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         tuple val(sampleId), path(gene_demulti_result), path(hash_demulti_result)
diff --git a/modules/single/gene_demultiplexing.nf b/modules/single/gene_demultiplexing.nf
index 2254bed..20d5bd4 100644
--- a/modules/single/gene_demultiplexing.nf
+++ b/modules/single/gene_demultiplexing.nf
@@ -24,7 +24,7 @@ process summary{
     publishDir "$projectDir/$params.outdir/$params.mode/gene_demulti", mode: 'copy'
     label 'small_mem'
     
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         val demuxlet_result
diff --git a/modules/single/hash_demulti/demuxem.nf b/modules/single/hash_demulti/demuxem.nf
index ff872fa..5e1f734 100644
--- a/modules/single/hash_demulti/demuxem.nf
+++ b/modules/single/hash_demulti/demuxem.nf
@@ -5,7 +5,7 @@ process demuxem{
     publishDir "$projectDir/$params.outdir/$params.mode/hash_demulti/demuxem", mode:'copy'
     label 'small_mem'
     
-    conda "python=3.9 bioconda::pegasuspy 'pandas<2.0.0' demuxEM"
+    conda "python bioconda::pegasuspy pandas demuxEM scanpy"
 
     input:
         path raw_rna_matrix_dir, stageAs: "rna_data_${params.rna_matrix_demuxem}"
diff --git a/modules/single/hash_demultiplexing.nf b/modules/single/hash_demultiplexing.nf
index 6a109ec..bde9466 100644
--- a/modules/single/hash_demultiplexing.nf
+++ b/modules/single/hash_demultiplexing.nf
@@ -15,7 +15,7 @@ process summary{
     publishDir "$projectDir/$params.outdir/$params.mode/hash_demulti", mode: 'copy'
     label 'small_mem'
 
-    conda "python=3.9 'pandas<2.0' scanpy muon numpy"
+    conda "pandas scanpy mudata"
 
     input:
         val demuxem_result
diff --git a/nextflow.config b/nextflow.config
index 5f59f4e..60866af 100644
--- a/nextflow.config
+++ b/nextflow.config
@@ -2,7 +2,7 @@ params {
   outdir = "result"
   mode = "rescue"
   generate_anndata = "True"
-  generate_mudata = "False"
+  generate_mudata = "True"
   multi_input = null  // run only one sample
 
   // hashing-based deconvolution
@@ -247,7 +247,7 @@ params {
   vireo_out = "vireo_out"
  
   // souporcell
-  souporcell = "False"
+  souporcell = "True"
   souporcell_preprocess = "False"
   threads = 5
   ploidy = 2
@@ -437,7 +437,7 @@ profiles {
     singularity {
         singularity.enabled    = true
         singularity.runOptions = "--bind $PWD"
-        singularity.cacheDir = "$PWD"
+        singularity.cacheDir   = "$PWD"
         conda.enabled          = false
         docker.enabled         = false
         podman.enabled         = false
@@ -447,10 +447,17 @@ profiles {
     }
     test { 
         includeConfig 'test.config'
+    }
+    conda_singularity { 
         singularity.enabled    = true
         singularity.runOptions = "--bind $PWD"
-        singularity.cacheDir = "$PWD"
-        conda.enabled          = true       
+        singularity.cacheDir   = "$PWD"
+        conda.enabled          = true
+        docker.enabled         = false
+        podman.enabled         = false
+        shifter.enabled        = false
+        charliecloud.enabled   = false
+        apptainer.enabled      = false   
     }
 }
 
diff --git a/test_data/temporary_hto/matrix.mtx b/test_data/temporary_hto/matrix.mtx
deleted file mode 100644
index e3e87d9..0000000
--- a/test_data/temporary_hto/matrix.mtx
+++ /dev/null
@@ -1,1002 +0,0 @@
-%%MatrixMarket matrix coordinate integer general
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diff --git a/test_data/temporary_hto/matrix_hto611905d177.mtx.gz b/test_data/temporary_hto/matrix_hto611905d177.mtx.gz
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