diff --git a/psmfragmentation/psmfragmentation.py b/psmfragmentation/psmfragmentation.py
index b0a882c..81d171f 100644
--- a/psmfragmentation/psmfragmentation.py
+++ b/psmfragmentation/psmfragmentation.py
@@ -113,9 +113,7 @@ def __init__(self, obj):
         super(TabularResults, self).__init__()
         self._results = {}
         self._tolerance = obj['tolerance']
-        self._keys = ('scan_number', 'scan_file', 'max_cont_b', 'max_cont_y', 'pct_pks_matched',
-            'num_peaks_unmatched_10pct', 'tic', 'precursor_mz', 'retention_time')
-    
+        
     def _unmatched_peaks(self):
         for _, entry in self._results.items():
             max_int_threshold = max(entry['scan']['intensity'], default=0) * .10
@@ -139,10 +137,12 @@ def _fragment_percent(self):
             self._results[psmid]['pct_b_peaks_matched'] = round((num_match_b/num_b) * 100.0, 2)
             self._results[psmid]['pct_y_peaks_matched'] = round((num_match_y/num_y) * 100.0, 2)
 
-    def add_psm(self, psm, scan_file_name):
-        obj = {k:v for k,v in psm.items()}
-        self._results[psm['ID']] = obj
-        self._results[psm['ID']]['scanFile'] = scan_file_name
+    #def add_psm(self, psm, scan_file_name):
+    def add_psm(self, conf_obj):
+        obj = {k:v for k,v in conf_obj['psm'].items()}
+        self._results[conf_obj['psm']['ID']] = obj
+        self._results[conf_obj['psm']['ID']]['scanFile'] = conf_obj['scan_filename']
+        self._results[conf_obj['psm']['ID']]['peptideSequence'] = conf_obj['pepseq']
 
     def add_ionruns(self, psm_id, matches):
         self._results[psm_id]['matched_peaks'] = matches
@@ -158,9 +158,9 @@ def add_frags(self, psm_id, fragments):
     def generate_output(self):
         self._fragment_percent()
         self._unmatched_peaks()
-        r_keys = ('spectrumID', 'spectrumTitle', 'scanFile','PSPSMScore', 'PSPSMConfidence','TIC','max_b_run','max_y_run','pct_b_peaks_matched', 'pct_y_peaks_matched','num_peaks_unmatched_10pct')
-        with open('results.txt', 'w') as f:
-            f.write(f"spectrumID,spectrumTitle,scanFile,PSScore,PSConfidence,TIC,Max_B_Run, Max_Y_Run,PCT_B_Matched, PCT_Y_Matched,Num_10Pct_Peaks_Unmatched")
+        r_keys = ('peptideSequence','spectrumID', 'spectrumTitle', 'scanFile','PSPSMScore', 'PSPSMConfidence','TIC','max_b_run','max_y_run','pct_b_peaks_matched', 'pct_y_peaks_matched','num_peaks_unmatched_10pct')
+        with open('results.csv', 'w') as f:
+            f.write(f"sequence,spectrumID,spectrumTitle,scanFile,PSScore,PSConfidence,TIC,Max_B_Run, Max_Y_Run,PCT_B_Matched, PCT_Y_Matched,Num_10Pct_Peaks_Unmatched")
             f.write(os.linesep)
             for _, entry in self._results.items():
                 line = ''
@@ -618,7 +618,7 @@ def score_psms(db_path, sequence_file, ion_types=('b', 'b-H2O', 'b-NH3','y', 'y-
                     logger.info(f"No consecutive ion run for {pep_seq}")
                 else:
                     #add psm to tabular results
-                    tabular_results.add_psm(tp, scan['scanFile'])
+                    tabular_results.add_psm({'psm':tp, 'scan_filename':scan['scanFile'], 'pepseq':pep_seq})
                     tabular_results.add_ionruns(tp['ID'], matched_peaks)
                     tabular_results.add_scan(tp['ID'], {'mz': _to_float(scan['mzValues']), 'intensity': _to_float(scan["intensities"])})
                     tabular_results.add_frags(tp['ID'], frags)