diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 00000000..21f5e727
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+# Never modify line endings of mzML files
+*.mzML* -crlf
diff --git a/README.rst b/README.rst
index d9646989..2a6cf647 100755
--- a/README.rst
+++ b/README.rst
@@ -6,8 +6,8 @@ Introduction
 .. image:: https://travis-ci.org/pymzml/pymzML.svg?branch=master
     :target: https://travis-ci.org/pymzml/pymzML
 
-.. image:: https://ci.appveyor.com/api/projects/status/4nlw52a9qn22921d?svg=true
-   :target: https://ci.appveyor.com/project/fufezan-lab/pymzml
+.. image:: https://ci.appveyor.com/api/projects/status/e5reb5xw74jfqk2v/branch/dev?svg=true
+   :target: https://ci.appveyor.com/api/projects/status/e5reb5xw74jfqk2v/branch/dev?svg=true
    :alt: AppVeyor CI status
 
 .. image:: https://readthedocs.org/projects/pymzml/badge/?version=latest
@@ -82,10 +82,9 @@ pymzML is an extension to Python that offers
 Implementation
 **************
 
-pymzML requires Python3.4+.
+pymzML requires Python3.5+.
 The module is freely available on pymzml.github.com or pypi,
-published under MIT license and requires no additional modules to be installed, but can
-optionally use numpy.
+published under MIT license and only requires numpy and regex, however there are several optional dependencies for extended functionality like interactive plotting and deconvolution.
 
 
 ********
@@ -111,7 +110,7 @@ doi: https://doi.org/10.1093/bioinformatics/bty046
 Installation
 ************
 
-pymzML requires `Python`_ 3.4 or higher.
+pymzML requires `Python`_ 3.5 or higher.
 
 .. note::
 
@@ -134,6 +133,15 @@ Download pymzML using `GitHub`_ **or** the zip file:
 .. _GitHub:
    https://github.com/pymzML/pymzml
 
+* pypi version::
+
+   user@localhost:~$ pip install pymzml # install standard version
+   user@localhost:~$ pip install "pymzml[plot]" # with plotting support
+   user@localhost:~$ pip install "pymzml[pynumpress]" # with pynumpress support
+   user@localhost:~$ pip install "pymzml[deconvolution]" # with deconvolution support using ms_deisotope
+   user@localhost:~$ pip install "pymzml[full]" # full featured
+
+
 If you have troubles installing the dependencies, install numpy first separately,
 since pynumpress requires numpy to be installed.
 
@@ -146,7 +154,7 @@ Testing
 
 To test the package and correct installation::
 
-    nosetests tests/*.py
+    tox
 
 
 *************
diff --git a/docs/requirements.txt b/docs/requirements.txt
index c28cfaa1..3b934cbe 100755
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,3 +1,3 @@
-sphinx==2.3.1
+sphinx==3.0.3
 sphinx_rtd_theme==0.4.3
 regex
diff --git a/docs/source/quick_start.rst b/docs/source/quick_start.rst
index f6bb7caf..ed2741c8 100755
--- a/docs/source/quick_start.rst
+++ b/docs/source/quick_start.rst
@@ -33,4 +33,27 @@ no matter if an index was included into the file or not.
     spectrum_with_id_2540 = run[ 2540 ]
 
 
+Reading mzML indices with a custom regular expression
+------------------------------------------------------
+
+When reading mzML files with indices wich is not an integer or contains "scan=1" or similar,
+you can set a custom regex to parse the index when initializing the reader.
+
+Say for example you have an index as in the example file Manuels_customs_ids.mzML:
+    <offset idRef="ManuelsCustomID=1 diesdas">4026</offset>
+
+.. code-block:: python
+
+    #!/usr/bin/env python
+    import pymzml
+    import re
+
+    index_re = re.compile(
+        b'.*idRef="ManuelsCustomID=(?P<ID>.*) diesdas">(?P<offset>[0-9]*)</offset>'
+    )
+    run = pymzml.run.Reader(your_file_path, index_regex=index_re)
+    spec_1 = run[1]
+
+The regular expression has to contain a group called ID and a group called offset.
+Also be aware that your regex need to be a byte string.
 
diff --git a/example_scripts/spectrum_viewer.py b/example_scripts/spectrum_viewer.py
deleted file mode 100755
index 3f9c667c..00000000
--- a/example_scripts/spectrum_viewer.py
+++ /dev/null
@@ -1,193 +0,0 @@
-#!/usr/bin/env python3
-
-import sys
-import os
-
-import pymzml
-
-import plotly.graph_objs as go
-
-import dash
-import dash_core_components as dcc
-import dash_html_components as html
-
-
-print('loading run...')
-run = pymzml.run.Reader(sys.argv[1])
-
-all_ids = []
-for spec_id, offset in run.info['offset_dict'].items():
-    try:
-        all_ids.append(int(spec_id))
-    except:
-        continue
-FIRST_SPECTRUM_ID = min(all_ids)
-LAST_SPECTRUM_ID = max(all_ids)
-
-p = pymzml.plot.Factory()
-p.new_plot()
-
-tic_x=[]
-tic_y=[]
-for x,y in run['TIC'].peaks():
-    tic_x.append(x)
-    tic_y.append(y)
-max_tic = max(tic_y)
-
-tic_annotation = []
-
-for n, RT in enumerate(tic_x):
-    tic_annotation.append(
-        'RT: {0:1.3f}<br>ID: {1}'.format(
-            RT,
-            all_ids[n]
-        )
-    )
-
-app = dash.Dash(__name__)
-
-app.layout = html.Div([
-    dcc.Graph(
-        id='spectrum-plot',
-        style={
-            'fontFamily': 'Helvetica',
-        }
-    ),
-    html.H3(
-        children='Please specify spectrum ID',
-        style={
-            'fontFamily': 'Helvetica',
-        }
-    ),
-    dcc.Input(
-        id='spectrum-input-field',
-        value=FIRST_SPECTRUM_ID,
-        type='text',
-        style={
-            'width': '20%',
-            'height': '30px',
-            'lineHeight': '30px',
-            'borderWidth': '1px',
-            'borderStyle': 'dashed',
-            'borderRadius': '5px',
-            'fontFamily': 'Helvetica',
-            'fontSize': '130%'
-        }
-    ),
-    dcc.Graph(
-        id='tic-plot',
-    ),
-])
-
-
-def get_spectrum(spectrum_id):
-    return run[spectrum_id]
-
-def sanitize_id(spectrum_id_from_input):
-    if spectrum_id_from_input not in [None, '']:
-        spectrum_id  = int(spectrum_id_from_input)
-    else:
-        spectrum_id = FIRST_SPECTRUM_ID
-    if spectrum_id < FIRST_SPECTRUM_ID:
-        spectrum_id = FIRST_SPECTRUM_ID
-    if spectrum_id > LAST_SPECTRUM_ID:
-        spectrum_id = LAST_SPECTRUM_ID
-    return spectrum_id
-
-
-@app.callback(
-    dash.dependencies.Output('tic-plot', 'figure'),
-    [
-        dash.dependencies.Input('spectrum-input-field', 'value'),
-    ]
-)
-def update_TIC(spectrum_id_from_input=None):
-    spectrum_id = sanitize_id(spectrum_id_from_input)
-    spectrum = get_spectrum(spectrum_id)
-    rt = spectrum.scan_time[0]
-    figure = {
-        'data':[
-            {
-                'x':tic_x,
-                'y':tic_y,
-                'line':{'color':'black'},
-                'text':tic_annotation
-            },
-            {
-                'x':[rt, rt],
-                'y':[0,max_tic],
-                'line':{'color':'red', 'width':2}, 
-                'text':[
-                    '',
-                    'RT: {0}<br>ID: {1}'.format(
-                        rt,
-                        spectrum_id
-                    )
-                ]
-            }
-        ],
-        'layout':go.Layout(
-            xaxis={ 'title': 'RT', 'autorange':False, 'range':[0,max(tic_x)]},
-            yaxis={'title': 'Intensity',},
-            margin={'l': 40, 'b': 40, 't': 40, 'r': 10},
-            legend={'x': 0, 'y': 1},
-            hovermode='closest',
-            showlegend=False,
-            title = 'TIC'
-        )
-    }
-    return figure
-
-
-@app.callback(
-    dash.dependencies.Output('spectrum-plot', 'figure'),
-    [
-        dash.dependencies.Input('spectrum-input-field', 'value'),
-    ]
-)
-def trigger_new_spec_from_input( spectrum_id_from_input=None):
-    spectrum_id = sanitize_id(spectrum_id_from_input)
-    spectrum = get_spectrum(spectrum_id)
-    return update_figure(spectrum)
-
-
-def update_figure(spectrum):
-    spectrum_plot = p.add(
-        spectrum.peaks('centroided'),
-        color = ( 0, 0, 0 ),
-        style = 'sticks',
-        name = 'peaks'
-    )
-    new_spectrum_plot={}
-    new_spectrum_plot['x'] = spectrum_plot['x'] 
-    new_spectrum_plot['y'] = spectrum_plot['y']
-    new_spectrum_plot['line']={'color':'black'}
-    # print(spectrum_plot)
-    title = 'Spectrum {0} @ RT: {1} [{2}s] of run {3}'.format(
-        spectrum.ID,
-        spectrum.scan_time[0],
-        spectrum.scan_time[1],
-        os.path.basename(sys.argv[1])
-    )
-    if spectrum.ms_level == 2:
-        tmp_selected_precursors = spectrum.selected_precursors[0]
-        format_str_template = '<br>'
-        for key, format_template in [ ('mz',' Precursor m/z: {0}'), ('i', '; intensity {0:1.2e}'), ('charge','; charge: {0}') ]:
-            if key in tmp_selected_precursors.keys():
-                format_str_template += format_template.format(tmp_selected_precursors[key])
-        title += format_str_template
-    return {
-        'data': [new_spectrum_plot],
-        'layout': go.Layout(
-            xaxis={ 'title': 'm/z'},
-            yaxis={'title': 'Intensity',},
-            margin={'l': 40, 'b': 40, 't': 80, 'r': 10},
-            legend={'x': 0, 'y': 1},
-            hovermode='closest',
-            title = title
-        )
-    }
-
-
-if __name__ == '__main__':
-    app.run_server(debug=True)
diff --git a/pymzml/file_classes/standardMzml.py b/pymzml/file_classes/standardMzml.py
index fe2b038d..b398d51d 100755
--- a/pymzml/file_classes/standardMzml.py
+++ b/pymzml/file_classes/standardMzml.py
@@ -42,7 +42,7 @@ class StandardMzml(object):
     """
     """
 
-    def __init__(self, path, encoding, build_index_from_scratch=False):
+    def __init__(self, path, encoding, build_index_from_scratch=False, index_regex=None):
         """
         Initalize Wrapper object for standard mzML files.
 
@@ -50,6 +50,7 @@ def __init__(self, path, encoding, build_index_from_scratch=False):
             path (str)     : path to the file
             encoding (str) : encoding of the file
         """
+        self.index_regex = index_regex
         self.path = path
         self.file_handler = self.get_file_handler(encoding)
         self.offset_dict = dict()
@@ -131,7 +132,6 @@ def __getitem__(self, identifier):
         elif type(identifier) == str:
             return self._search_string_identifier(identifier)
         else:
-            # spectrum = self._interpol_search(identifier)
             spectrum = self._binary_search(identifier)
 
         return spectrum
@@ -153,7 +153,6 @@ def _binary_search(self, target_index):
         jump_history = {'forwards': 0, 'backwards': 0}
         # This will be used if no spec was found at all during a jump
         # self._average_bytes_per_spec *= 10
-        # print(f"self.seek_list : {self.seek_list}")
         with open(self.path, "rb") as seeker:
             if target_index not in self.offset_dict.keys():
                 for jump in range(40):
@@ -184,13 +183,6 @@ def _binary_search(self, target_index):
                     average_spec_between_m1_p1 = int(
                         round(byte_diff_m1_p1 / scan_diff_m1_p1)
                     )
-                    # print("\n------------")
-                    # print(f"jump {jump}")
-                    # print(f"insert_pos {insert_position}")
-                    # print(f"average_spec_between_m1_p1 {average_spec_between_m1_p1}")
-                    # print(f"diff target to m1 / spec_offset_m1 {spec_offset_m1}")
-                    # print(f"diff target to p1 / spec_offset_p1 {spec_offset_p1}")
-
                     # which side are we closer to ...
                     if spec_offset_m1 < spec_offset_p1:
                         # print("Closer to m1 - jumping forward")
@@ -205,7 +197,6 @@ def _binary_search(self, target_index):
                             # and read chunks until found
                             byte_offset = element_before[1]
                     else:
-                        # print("Closer to p1 - jumping backwards")
                         jump_direction = 'backwards'
                         jump_history['forwards'] = 0
                         jump_history['backwards'] += 1
@@ -213,11 +204,6 @@ def _binary_search(self, target_index):
                             offset_scale * average_spec_between_m1_p1 * spec_offset_p1
                         )
                     byte_offset = int(byte_offset)
-                    # print(f"jump_history {jump_history}")
-                    # print(f"bytes offset {byte_offset}")
-                    # print(f"offset_scale {offset_scale}")
-                    # print(f"seek_list: {min(self.seek_list)} - {max(self.seek_list)} .. n: {len(self.seek_list)}")
-                    # print(f"seek_list[:-10]: {self.seek_list[:10]}")
                     found_scan = False
                     chunk = b""
                     break_outer = False
@@ -227,7 +213,6 @@ def _binary_search(self, target_index):
                             max([os.SEEK_SET + byte_offset + x * chunk_size, 1])
                         )
                         chunk += seeker.read(chunk_size)
-                    # print(f'read {len(chunk)}')
                     matches = re.finditer(regex_patterns.SPECTRUM_OPEN_PATTERN, chunk)
                     for _match_number, match in enumerate(matches):
                         if match is not None:
@@ -248,7 +233,6 @@ def _binary_search(self, target_index):
                                     offset_scale = 1
 
                             if scan in self.offset_dict.keys():
-                                # print("Have seen this scan {scan} already")
                                 continue
                             found_scan = True
                             new_entry = (
@@ -274,12 +258,10 @@ def _binary_search(self, target_index):
                         break
 
             start = self.offset_dict[target_index]
-            # print(f"reading spec at pos {start}")
             seeker.seek(start[0])
             match = None
             data = b""
             while b"</spectrum>" not in data:
-                # print("reading to end")
                 data += seeker.read(chunk_size)
             end = data.find(b"</spectrum>")
             seeker.seek(start[0])
@@ -308,13 +290,6 @@ def _build_index(self, from_scratch=False):
         """
         # Declare the pre-seeker
         seeker = self.get_binary_file_handler()
-        # Reading last 1024 bytes to find chromatogram Pos and SpectrumIndex Pos
-        index_list_offset_pattern = re.compile(
-            b"<indexListOffset>(?P<indexListOffset>[0-9]*)</indexListOffset>"
-        )
-        chromatogram_offset_pattern = re.compile(
-            b'(?P<WTF>[nativeID|idRef])="TIC">(?P<offset>[0-9]*)</offset'
-        )
         self.offset_dict["TIC"] = None
         seeker.seek(0, 2)
         index_found = False
@@ -331,7 +306,7 @@ def _build_index(self, from_scratch=False):
                 break
                 # File is smaller than 10kbytes ...
             for line in seeker:
-                match = chromatogram_offset_pattern.search(line)
+                match = regex_patterns.CHROMATOGRAM_OFFSET_PATTERN.search(line)
                 if match:
                     self.offset_dict["TIC"] = int(bytes.decode(match.group("offset")))
 
@@ -340,16 +315,12 @@ def _build_index(self, from_scratch=False):
                     spec_byte_offset = int(bytes.decode(match_spec.group("offset")))
                     sanity_check_set.add(spec_byte_offset)
 
-                match = index_list_offset_pattern.search(line)
+                match = regex_patterns.INDEX_LIST_OFFSET_PATTERN.search(line)
                 if match:
                     index_found = True
-                    # print(int(match.group('indexListOffset').decode('utf-8')))
-                    # print(line)
-                    # exit(1)
                     index_list_offset = int(
                         match.group("indexListOffset").decode("utf-8")
                     )
-                    # break
 
             if index_found is True and self.offset_dict["TIC"] is not None:
                 break
@@ -365,33 +336,42 @@ def _build_index(self, from_scratch=False):
                 if match_spec and match_spec.group("nativeID") == b"":
                     match_spec = None
                 match_sim = sim_index_pattern.search(line)
-                if match_spec:
-                    offset = int(bytes.decode(match_spec.group("offset")))
-                    native_id = int(bytes.decode(match_spec.group("nativeID")))
-                    self.offset_dict[native_id] = offset
-                elif match_sim:
-                    offset = int(bytes.decode(match_sim.group("offset")))
-                    native_id = bytes.decode(match_sim.group("nativeID"))
-                    # if native_id == 'DECOY_126104_C[160]NVVISGGTGSGK/2_y10':
-                    try:
-                        native_id = int(
-                            regex_patterns.SPECTRUM_ID_PATTERN.search(native_id).group(
-                                1
+                if self.index_regex is None:
+                    if match_spec:
+                        offset = int(bytes.decode(match_spec.group("offset")))
+                        native_id = int(bytes.decode(match_spec.group("nativeID")))
+                        self.offset_dict[native_id] = offset
+                    elif match_sim:
+                        offset = int(bytes.decode(match_sim.group("offset")))
+                        native_id = bytes.decode(match_sim.group("nativeID"))
+                        try:
+                            native_id = int(
+                                regex_patterns.SPECTRUM_ID_PATTERN2.search(native_id).group(
+                                    2
+                                )
                             )
-                        )
-                        # exit(1)
-                    except AttributeError:
-                        # match is None and has no attribute group,
-                        # so use the whole string as ID
-                        pass
-                    self.offset_dict[native_id] = (offset,)
+                        except AttributeError:
+                            # match is None and has no attribute group,
+                            # so use the whole string as ID
+                            pass
+                        self.offset_dict[native_id] = (offset,)
+                else:
+                    match = self.index_regex.search(line)
+                    if match:
+                        native_id = match.group("ID")
+                        try:
+                            native_id = int(native_id)
+                        except ValueError:
+                            pass
+                        offset = match.group("offset")
+                        self.offset_dict[native_id] = (offset,)
 
         elif from_scratch is True:
             seeker.seek(0)
             self._build_index_from_scratch(seeker)
         else:
             print('[Warning] Not index found and build_index_from_scratch is False')
-        
+
         seeker.close()
 
 
@@ -532,7 +512,6 @@ def _interpol_search(self, target_index, chunk_size=8, fallback_cutoff=100):
 
                 self.offset_dict[current_index] = (spec_start_offset,)
                 if current_index in used_indices:
-                    # seeker.close()
                     if current_index > target_index:
                         jumper_scaling -= 0.1
                     else:
@@ -543,7 +522,6 @@ def _interpol_search(self, target_index, chunk_size=8, fallback_cutoff=100):
                 dist = current_index - target_index
                 if dist < -1 and dist > -(fallback_cutoff):
                     spectrum = self._search_linear(seeker, target_index)
-                    # seeker.close()
                     spectrum_found = True
                     break
                 elif dist > 0 and dist < fallback_cutoff:
@@ -560,7 +538,6 @@ def _interpol_search(self, target_index, chunk_size=8, fallback_cutoff=100):
                             )
                     seeker.seek(current_position)
                     spectrum = self._search_linear(seeker, target_index)
-                    # seeker.close()
                     spectrum_found = True
                     break
 
@@ -571,7 +548,6 @@ def _interpol_search(self, target_index, chunk_size=8, fallback_cutoff=100):
                     seeker.seek(start)
                     self.offset_dict[current_index] = (start, end)
                     xml_string = seeker.read(end - start)
-                    # seeker.close()
                     spectrum = spec.Spectrum(XML(xml_string), measured_precision=5e-6)
                     spectrum_found = True
                     break
@@ -665,9 +641,12 @@ def _read_extremes(self):
                 match = regex_patterns.SPECTRUM_OPEN_PATTERN_SIMPLE.search(buffer)
                 if match is not None:
                     id_match = regex_patterns.SPECTRUM_ID_PATTERN_SIMPLE.search(buffer)
-                    first_scan = int(
-                        re.search(b"[0-9]*$", id_match.group("id")).group()
-                    )
+                    try:
+                        first_scan = int(
+                            re.search(b"[0-9]*$", id_match.group("id")).group()
+                        )
+                    except ValueError:
+                        first_scan = 0
                     #
                     seek_list.append(
                         (first_scan, seeker.tell() - chunk_size + match.start())
diff --git a/pymzml/file_interface.py b/pymzml/file_interface.py
index 3a55089c..92f214ca 100755
--- a/pymzml/file_interface.py
+++ b/pymzml/file_interface.py
@@ -13,7 +13,7 @@
 class FileInterface(object):
     """Interface to different mzML formats."""
 
-    def __init__(self, path, encoding, build_index_from_scratch=False):
+    def __init__(self, path, encoding, build_index_from_scratch=False, index_regex=None):
         """
         Initialize a object interface to mzML files.
 
@@ -24,6 +24,7 @@ def __init__(self, path, encoding, build_index_from_scratch=False):
         """
         self.build_index_from_scratch = build_index_from_scratch
         self.encoding = encoding
+        self.index_regex = index_regex
         self.file_handler = self._open(path)
         self.offset_dict = self.file_handler.offset_dict
 
@@ -55,7 +56,7 @@ def _open(self, path_or_file):
             else:
                 return standardGzip.StandardGzip(path_or_file, self.encoding)
         return standardMzml.StandardMzml(
-            path_or_file, self.encoding, self.build_index_from_scratch
+            path_or_file, self.encoding, self.build_index_from_scratch, index_regex=self.index_regex
         )
 
     def _indexed_gzip(self, path):
diff --git a/pymzml/plot.py b/pymzml/plot.py
index 92587599..d5a21713 100755
--- a/pymzml/plot.py
+++ b/pymzml/plot.py
@@ -37,7 +37,7 @@
 try:
     import plotly.offline as plt
     import plotly.graph_objs as go
-    from plotly import tools
+    from plotly import subplots
 except ImportError:
     warnings.warn("Plotly is required for plotting support.", ImportWarning)
 
@@ -564,7 +564,7 @@ def save(self, filename=None, mz_range=None, int_range=None, layout=None):
         plot_number = len(self.plots)
         rows, cols = int(math.ceil(plot_number / float(2))), 2
         if plot_number % 2 == 0:
-            my_figure = tools.make_subplots(
+            my_figure = subplots.make_subplots(
                 rows=rows,
                 cols=cols,
                 vertical_spacing=0.6 / rows,
@@ -573,7 +573,7 @@ def save(self, filename=None, mz_range=None, int_range=None, layout=None):
         else:
             specs = [[{}, {}] for x in range(rows - 1)]
             specs.append([{"colspan": 2}, None])
-            my_figure = tools.make_subplots(
+            my_figure = subplots.make_subplots(
                 rows=rows,
                 cols=cols,
                 vertical_spacing=0.6 / rows,
diff --git a/pymzml/regex_patterns.py b/pymzml/regex_patterns.py
index 304de803..00839c9a 100755
--- a/pymzml/regex_patterns.py
+++ b/pymzml/regex_patterns.py
@@ -24,6 +24,7 @@
 """
 SPECTRUM_PATTERN3 = regex.compile(r"((\w+)=(\w+\s*))+")
 SPECTRUM_ID_PATTERN = re.compile(r'="{0,1}([0-9]*)"{0,1}>{0,1}$')
+SPECTRUM_ID_PATTERN2 = re.compile(r'(scan|scanId)=(\d+)')
 """
 Simplified spectrum id regex. Greedly catches ints at the end of line
 """
@@ -70,3 +71,11 @@
     r"<\s*(chromatogram|spectrum)\s*(id=(\".*?\")|index=\".*?\")\s(id=(\".*?\"))*\s*.*\sdefaultArrayLength=\"[0-9]+\">"
 )
 """Regex to catch combined chromatogram and spectrum patterns"""
+
+INDEX_LIST_OFFSET_PATTERN = re.compile(
+    b"<indexListOffset>(?P<indexListOffset>[0-9]*)</indexListOffset>"
+)
+
+CHROMATOGRAM_OFFSET_PATTERN = re.compile(
+    b'(?P<WTF>[nativeID|idRef])="TIC">(?P<offset>[0-9]*)</offset'
+)
diff --git a/pymzml/run.py b/pymzml/run.py
index a5e9caf3..22fc15bb 100755
--- a/pymzml/run.py
+++ b/pymzml/run.py
@@ -82,9 +82,11 @@ def __init__(
         obo_version=None,
         build_index_from_scratch=False,
         skip_chromatogram=True,
+        index_regex=None,
         **kwargs
     ):
         """Initialize and set required attributes."""
+        self.index_regex = index_regex
         self.build_index_from_scratch = build_index_from_scratch
         self.skip_chromatogram = skip_chromatogram
         if MS_precisions is None:
@@ -100,6 +102,7 @@ def __init__(
             None: 0.0001,  # if spectra does not contain ms_level information
                          # e.g. UV-chromatograms (thanks pyeguy) then ms_level is
                          # returned as None
+            0: 0.0001,
             1: 5e-6,
             2: 20e-6,
         }
@@ -107,6 +110,7 @@ def __init__(
 
         # File info
         self.info = ddict()
+        self.path_or_file = path_or_file
         if isinstance(path_or_file, str):
             self.info["file_name"] = path_or_file
             self.info["encoding"] = self._determine_file_encoding(path_or_file)
@@ -165,6 +169,9 @@ def __next__(self):
                     spectrum.calling_instance = self
                     return spectrum
             elif event == "END":
+                # reinit iter
+                self.info["file_object"] = self._open_file(self.path_or_file)
+                self.iter = self._init_iter()
                 raise StopIteration
 
     def __getitem__(self, identifier):
@@ -216,6 +223,7 @@ def _open_file(self, path_or_file):
             path_or_file,
             self.info["encoding"],
             build_index_from_scratch=self.build_index_from_scratch,
+            index_regex=self.index_regex
         )
 
     def _guess_encoding(self, mzml_file):
diff --git a/pymzml/spec.py b/pymzml/spec.py
index 7a046893..a1ddb61c 100755
--- a/pymzml/spec.py
+++ b/pymzml/spec.py
@@ -443,6 +443,7 @@ def __init__(self, element=ElementTree.Element(""), measured_precision=5e-6):
         self._reprofiled_peaks = None
         self._scan_time = None
         self._scan_time_unit = None
+        self._scan_time_in_minutes = None
         self._t_mass_set = None
         self._t_mz_set = None
         self._TIC = None
@@ -626,12 +627,14 @@ def __getitem__(self, accession):
             return_val = self.ID
         else:
             if not accession.startswith("MS:"):
-                accession = self.calling_instance.OT[accession]["id"]
+                try:
+                    accession = self.calling_instance.OT[accession]["id"]
+                except TypeError:
+                    accession = '---'
             search_string = './/*[@accession="{0}"]'.format(accession)
-
             elements = []
             for x in self.element.iterfind(search_string):
-                val = x.attrib.get("value")
+                val = x.attrib.get("value", "")
                 try:
                     val = float(val)
                 except:
@@ -644,6 +647,8 @@ def __getitem__(self, accession):
                 return_val = elements[0]
             else:
                 return_val = elements
+        if return_val == '':
+            return_val = True
         return return_val
 
     def get(self, acc, default=None):
@@ -804,7 +809,7 @@ def ID(self):
                     except ValueError:
                         self._ID = match.group(1)
                 else:
-                    self._ID = ""
+                    self._ID = self.element.get("id")
         return self._ID
 
     @property
@@ -817,14 +822,18 @@ def id_dict(self):
         """
         if self._id_dict is None:
             tuples = []
-            captures = regex_patterns.SPECTRUM_PATTERN3.match(
+            match = regex_patterns.SPECTRUM_PATTERN3.match(
                 self.element.attrib["id"]
-            ).captures(1)
-            for element in captures:
-                k, v = element.strip().split("=")
-                v = int(v)
-                tuples.append([k, v])
-            self._id_dict = dict(tuples)
+            )
+            if match is not None:
+                captures = match.captures(1)
+                for element in captures:
+                    k, v = element.strip().split("=")
+                    v = int(v)
+                    tuples.append([k, v])
+                self._id_dict = dict(tuples)
+            else:
+                self._id_dict = {}
         return self._id_dict
 
     @property
@@ -895,18 +904,17 @@ def scan_time_in_minutes(self):
         Returns:
             scan_time (float):
         """
-
-        self._scan_time, time_unit = self.scan_time
-        if self._scan_time_unit.lower() == "second":
-            self._scan_time /= 60.0
-        elif self._scan_time_unit.lower() == "minute":
-            pass
-        elif self._scan_time_unit.lower() == "hour":
-            self._scan_time *= 60.0
-            pass
-        else:
-            raise Exception("Time unit '{0}' unknown".format(self._scan_time_unit))
-        return self._scan_time
+        if self._scan_time_in_minutes is None:
+            self._scan_time, time_unit = self.scan_time
+            if self._scan_time_unit.lower() == "second":
+                self._scan_time_in_minutes = self._scan_time / 60.0
+            elif self._scan_time_unit.lower() == "minute":
+                self._scan_time_in_minutes = self._scan_time
+            elif self._scan_time_unit.lower() == "hour":
+                self._scan_time_in_minutes = self._scan_time * 60.0
+            else:
+                raise Exception("Time unit '{0}' unknown".format(self._scan_time_unit))
+        return self._scan_time_in_minutes
 
     @property
     def selected_precursors(self):
diff --git a/pymzml/version.txt b/pymzml/version.txt
index 7bf4b6a8..e30309f7 100755
--- a/pymzml/version.txt
+++ b/pymzml/version.txt
@@ -1 +1 @@
-2.4.6
+2.4.7
diff --git a/requirements.txt b/requirements.txt
index 41227b1f..9c8354aa 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,7 +1,6 @@
 # Installation
 numpy
-plotly==4.2.0
+plotly==4.4.1
 pynumpress==0.0.5
 regex
-ms_deisotope==0.0.9
-dash==1.5.1
+ms_deisotope==0.0.14
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 8ba5d1b0..dd45e8d6 100755
--- a/setup.py
+++ b/setup.py
@@ -21,7 +21,7 @@
             'obo/*.obo.gz'
         ]
     },
-    python_requires  = '>=3.4.0',
+    python_requires  = '>=3.5.0',
     install_requires = [
         'numpy >= 1.8.0',
         'regex',
@@ -34,7 +34,7 @@
         ],
         'plot': ['plotly<5.0'],
         'pynumpress': ['pynumpress>=0.0.4'],
-        'deconvolution': ['ms_deisotope'] 
+        'deconvolution': ['ms_deisotope==0.0.14'] 
     },
     description      = 'high-throughput mzML parsing',
     long_description = 'pymzML - python module for mzML parsing',
@@ -42,7 +42,7 @@
     author_email     = 'christian@fufezan.net',
     url              = 'http://pymzml.github.com',
     license          = 'The MIT license',
-    platforms        = 'any that supports python 3.4',
+    platforms        = 'any that supports python 3.5',
     classifiers      = [
         'Development Status :: 4 - Beta',
         'Environment :: Console',
@@ -55,7 +55,7 @@
         'Operating System :: POSIX',
         'Operating System :: POSIX :: SunOS/Solaris',
         'Operating System :: Unix',
-        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
         'Topic :: Scientific/Engineering :: Bio-Informatics',
         'Topic :: Scientific/Engineering :: Chemistry',
         'Topic :: Scientific/Engineering :: Medical Science Apps.',
diff --git a/tests/data/Manuels_custom_ids.mzML b/tests/data/Manuels_custom_ids.mzML
new file mode 100755
index 00000000..35014f97
--- /dev/null
+++ b/tests/data/Manuels_custom_ids.mzML
@@ -0,0 +1,549 @@
+<?xml version="1.0" encoding="ISO-8859-1"?>
+<indexedmzML xmlns="http://psi.hupo.org/ms/mzml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://psi.hupo.org/ms/mzml http://psidev.info/files/ms/mzML/xsd/mzML1.1.1_idx.xsd">
+  <mzML xmlns="http://psi.hupo.org/ms/mzml" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://psi.hupo.org/ms/mzml http://psidev.info/files/ms/mzML/xsd/mzML1.1.0.xsd" id="exp105-01-ds5562-Pos" version="1.1.0">
+    <cvList count="2">
+      <cv id="MS" fullName="Proteomics Standards Initiative Mass Spectrometry Ontology" version="3.25.0" URI="http://psidev.cvs.sourceforge.net/*checkout*/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo"/>
+      <cv id="UO" fullName="Unit Ontology" version="12:10:2011" URI="http://obo.cvs.sourceforge.net/*checkout*/obo/obo/ontology/phenotype/unit.obo"/>
+    </cvList>
+    <fileDescription>
+      <fileContent>
+        <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+      </fileContent>
+      <sourceFileList count="1">
+        <sourceFile id="RAW1" name="exp105-01-ds5562-Pos.raw" location="file:///C:/Xcalibur/data/exp105">
+          <cvParam cvRef="MS" accession="MS:1000768" name="Thermo nativeID format" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000563" name="Thermo RAW file" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000569" name="SHA-1" value="40cf85e46ecda3d8d71e067fb090e51f75d9a4b0"/>
+        </sourceFile>
+      </sourceFileList>
+    </fileDescription>
+    <referenceableParamGroupList count="1">
+      <referenceableParamGroup id="CommonInstrumentParams">
+        <cvParam cvRef="MS" accession="MS:1001911" name="Q Exactive" value=""/>
+        <cvParam cvRef="MS" accession="MS:1000529" name="instrument serial number" value="Exactive Series slot 0244"/>
+      </referenceableParamGroup>
+    </referenceableParamGroupList>
+    <softwareList count="2">
+      <software id="Xcalibur" version="2.2-164600/2.2.1.1646">
+        <cvParam cvRef="MS" accession="MS:1000532" name="Xcalibur" value=""/>
+      </software>
+      <software id="pwiz" version="3.0.3768">
+        <cvParam cvRef="MS" accession="MS:1000615" name="ProteoWizard" value=""/>
+      </software>
+    </softwareList>
+    <instrumentConfigurationList count="1">
+      <instrumentConfiguration id="IC1">
+        <referenceableParamGroupRef ref="CommonInstrumentParams"/>
+        <componentList count="4">
+          <source order="1">
+            <cvParam cvRef="MS" accession="MS:1000073" name="electrospray ionization" value=""/>
+            <cvParam cvRef="MS" accession="MS:1000057" name="electrospray inlet" value=""/>
+          </source>
+          <analyzer order="2">
+            <cvParam cvRef="MS" accession="MS:1000081" name="quadrupole" value=""/>
+          </analyzer>
+          <analyzer order="3">
+            <cvParam cvRef="MS" accession="MS:1000484" name="orbitrap" value=""/>
+          </analyzer>
+          <detector order="4">
+            <cvParam cvRef="MS" accession="MS:1000624" name="inductive detector" value=""/>
+          </detector>
+        </componentList>
+        <softwareRef ref="Xcalibur"/>
+      </instrumentConfiguration>
+    </instrumentConfigurationList>
+    <dataProcessingList count="1">
+      <dataProcessing id="pwiz_Reader_Thermo_conversion">
+        <processingMethod order="0" softwareRef="pwiz">
+          <cvParam cvRef="MS" accession="MS:1000544" name="Conversion to mzML" value=""/>
+        </processingMethod>
+        <processingMethod order="1" softwareRef="pwiz">
+          <cvParam cvRef="MS" accession="MS:1000035" name="peak picking" value=""/>
+          <userParam name="Thermo/Xcalibur peak picking"/>
+        </processingMethod>
+      </dataProcessing>
+    </dataProcessingList>
+    <run id="exp105-01-ds5562-Pos" defaultInstrumentConfigurationRef="IC1" startTimeStamp="2013-09-10T10:31:08Z" defaultSourceFileRef="RAW1">
+      <spectrumList count="2918" defaultDataProcessingRef="pwiz_Reader_Thermo_conversion">
+        <spectrum index="0" id="ManuelsCustomID=5 diesdas1" defaultArrayLength="917">
+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09703683" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.2183176e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="9.266164e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.065780639648" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="823.391845703125" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="0.0014658998" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p ESI Full ms [70.00-900.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="13.974979519844" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
+                <scanWindow>
+                  <cvParam cvRef="MS" accession="MS:1000501" name="scan window lower limit" value="70" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="900" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
+          </scanList>
+          <binaryDataArrayList count="2">
+            <binaryDataArray encodedLength="3992">
+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
+              <cvParam cvRef="MS" accession="MS:1000514" name="m/z array" value="" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+        </spectrum>
+        <spectrum index="4" id="ManuelsCustomID=5 diesdas5" defaultArrayLength="1123">
+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09703072" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.5768485e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.0922766e08"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.065620422363" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="846.521240234375" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="0.019297966" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p ESI Full ms [70.00-900.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="20.681066438556" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
+                <scanWindow>
+                  <cvParam cvRef="MS" accession="MS:1000501" name="scan window lower limit" value="70" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="900" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
+          </scanList>
+          <binaryDataArrayList count="2">
+            <binaryDataArray encodedLength="4764">
+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
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+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
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+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09702765" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.3517067e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="9.6721256e07"/>
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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09703489" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.3947114e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.0269418e08"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.048690795898" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="883.414489746094" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
+              <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="0.028213116" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p ESI Full ms [70.00-900.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
+              <cvParam cvRef="MS" accession="MS:1000927" name="ion injection time" value="19.81852017343" unitCvRef="UO" unitAccession="UO:0000028" unitName="millisecond"/>
+              <scanWindowList count="1">
+                <scanWindow>
+                  <cvParam cvRef="MS" accession="MS:1000501" name="scan window lower limit" value="70" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="900" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
+          </scanList>
+          <binaryDataArrayList count="2">
+            <binaryDataArray encodedLength="4528">
+              <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09702408" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.2689743e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="9.3238328e07"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.065742492676" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="888.178283691406" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
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+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p ESI Full ms [70.00-900.00]"/>
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+              <scanWindowList count="1">
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+                </scanWindow>
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+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
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+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.09702154" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.3886275e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.100936e08"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.048713684082" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
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+              <scanWindowList count="1">
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+          <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
+          <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
+          <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="74.0970336" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="1.2419386e07" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
+          <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="1.0005264e08"/>
+          <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="70.065757751465" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="898.746520996094" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+          <scanList count="1">
+            <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
+            <scan>
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+              <cvParam cvRef="MS" accession="MS:1000512" name="filter string" value="FTMS + p ESI Full ms [70.00-900.00]"/>
+              <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
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+              <scanWindowList count="1">
+                <scanWindow>
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+                  <cvParam cvRef="MS" accession="MS:1000500" name="scan window upper limit" value="900" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
+                </scanWindow>
+              </scanWindowList>
+            </scan>
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+      <chromatogramList count="1" defaultDataProcessingRef="pwiz_Reader_Thermo_conversion">
+        <chromatogram index="0" id="TIC" defaultArrayLength="2918">
+          <cvParam cvRef="MS" accession="MS:1000235" name="total ion current chromatogram" value=""/>
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+              <cvParam cvRef="MS" accession="MS:1000595" name="time array" value="" unitCvRef="UO" unitAccession="UO:0000031" unitName="minute"/>
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</binary>
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</binary>
+            </binaryDataArray>
+          </binaryDataArrayList>
+        </chromatogram>
+      </chromatogramList>
+    </run>
+  </mzML>
+  <indexList count="2">
+    <index name="spectrum">
+      <offset idRef="ManuelsCustomID=1 diesdas">4026</offset>
+      <offset idRef="ManuelsCustomID=2 diesdas">16851</offset>
+      <offset idRef="ManuelsCustomID=3 diesdas">29873</offset>
+      <offset idRef="ManuelsCustomID=4 diesdas">45699</offset>
+      <offset idRef="ManuelsCustomID=5 diesdas">60404</offset>
+      <offset idRef="ManuelsCustomID=6 diesdas">75194</offset>
+      <offset idRef="ManuelsCustomID=7 diesdas">89360</offset>
+      <offset idRef="ManuelsCustomID=8 diesdas">103569</offset>
+      <offset idRef="ManuelsCustomID=9 diesdas">118117</offset>
+      <offset idRef="ManuelsCustomID=10 diesdas">132417</offset>
+    </index>
+    <index name="chromatogram">
+      <offset idRef="TIC" info="just any number since not existent, ja">132417</offset>
+    </index>
+  </indexList>
+  <indexListOffset>210500</indexListOffset>
+  <fileChecksum>MZMLDemoFile</fileChecksum>
+</indexedmzML>
diff --git a/tests/main_reader_test.py b/tests/main_reader_test.py
index a6fa0d95..357314d0 100755
--- a/tests/main_reader_test.py
+++ b/tests/main_reader_test.py
@@ -4,6 +4,7 @@
 Part of pymzml test cases
 """
 import os
+import re
 import pymzml.run as run
 import unittest
 from pymzml.spec import Spectrum, Chromatogram
@@ -215,6 +216,21 @@ def test_readers_remeber_spawned_spectra(self):
         """
         pass
 
+    def test_read_custom_regex(self):
+        custom_regex_file = os.path.join(
+            os.path.dirname(__file__),
+            "data",
+            "Manuels_custom_ids.mzML"
+        )
+        reader = run.Reader(
+            custom_regex_file,
+            index_regex=re.compile(
+                b'.*idRef="ManuelsCustomID=(?P<ID>.*) diesdas">(?P<offset>[0-9]*)</offset>'
+            )
+        )
+        ids = sorted([k for k in reader.info['offset_dict'].keys() if k != 'TIC'])
+        assert ids == list(range(1, 11))
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=3)
diff --git a/tests/ms2_spec_test.py b/tests/ms2_spec_test.py
index 2d952136..42aab350 100755
--- a/tests/ms2_spec_test.py
+++ b/tests/ms2_spec_test.py
@@ -34,9 +34,11 @@ def setUp(self):
 
     def test_scan_time(self):
         scan_time = self.spec.scan_time_in_minutes()
+        scan_time2 = self.spec.scan_time_in_minutes()
         self.assertIsNotNone(scan_time)
         self.assertIsInstance(scan_time, float)
         self.assertEqual(round(scan_time, 4), round(28.96722412109367, 4))
+        self.assertEqual(scan_time, scan_time2)
 
     def test_select_precursors(self):
         selected_precursor = self.spec.selected_precursors
@@ -48,6 +50,12 @@ def test_select_precursors(self):
             selected_precursor, [{"mz": 443.711242675781, "i": 0.0, "charge": 2}]
         )
 
+    def test_ion_mode(self):
+        assert self.spec['positive scan'] is True
+
+    def test_ion_mode_non_existent(self):
+        assert self.spec['negative scan'] is None
+
     @unittest.skipIf(pymzml.spec.DECON_DEP is False, "ms_deisotope was not installed")
     def test_deconvolute_peaks(self):
         charge = 3