1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213
|
.. code-block:: python
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import copy
import os
import pymzml
def main():
"""
This script shows how to plot multiple spectra in one plot and
how to use label for the annotation of spectra.
The first plot is an MS1 spectrum with the annotated precursor ion.
The second plot is a zoom into the precursor isotope pattern.
The third plot is an annotated fragmentation spectrum (MS2) of the
peptide HLVDEPQNLIK from BSA.
These examples also show the use of 'layout' to define the appearance
of a plot.
usage:
./plot_spectrum_with_annotation.py
"""
# First we define some general layout attributes
layout = {
"xaxis": {
"title": "<i>m/z</i>",
"tickmode": "auto",
"showticklabels": True,
"ticklen": 5,
"tickwidth": 1,
"ticks": "outside",
"showline": True,
"showgrid": False,
},
"yaxis": {
"color": "#000000",
"tickmode": "auto",
"showticklabels": True,
"ticklen": 5,
"tickwidth": 1,
"ticks": "outside",
"showline": True,
"showgrid": False,
},
}
# The example BSA file will be used
example_file = os.path.join(
os.path.dirname(__file__), os.pardir, "tests", "data", "BSA1.mzML.gz"
)
# Define different precisions for MS1 and MS2
run = pymzml.run.Reader(example_file, MS_precisions={1: 5e-6, 2: 5e-4})
p = pymzml.plot.Factory()
plot_layout = {}
# Now that everything is set up, we can plot the MS1 spectrum
# Spectrum ID: 1574
p.new_plot(title="MS1 Spectrum")
ms1_spectrum = run[1574]
# The measured peaks are added as first trace
p.add(
ms1_spectrum.peaks("centroided"),
color=(0, 0, 0),
opacity=1,
style="sticks",
name="raw data plot 1",
)
# The label for the precursor ion is added as a seperate trace.
# Note that triangle.MS_precision is used here as a label.
# By zooming in at this peak one can therefore check if the measured
# peak fits into defined the mass accuracy range.
precursor_mz_calc = 435.9102
p.add(
[(precursor_mz_calc, "max_intensity", "theoretical precursor")],
color=(255, 0, 0),
opacity=0.6,
style="label.triangle.MS_precision",
name="theoretical precursor plot 1",
)
# Define the layout for the first subplot.
# The x- and y-axes of subplots are numbered, starting at 1.
for axis in layout.keys():
plot_layout["{0}1".format(axis)] = copy.copy(layout[axis])
# Now we can add a second plot, the same way as above but as a zoom-in.
# Therefore, we define a mz_range
p.new_plot(title="MS1 Spectrum Zoom")
p.add(
ms1_spectrum.peaks("centroided"),
color=(0, 0, 0),
opacity=1,
style="sticks",
name="raw data plot 2",
plot_num=1,
mz_range=[435.7, 437],
)
p.add(
[(precursor_mz_calc, "max_intensity", "theoretical precursor")],
color=(255, 0, 0),
opacity=0.3,
plot_num=1,
style="label.triangle.MS_precision",
name="theoretical precursor plot 2",
)
# The mz_range can be included in the layout as well.
# In contrast to mz_range in the add() function, which limits the included
# datapoints, the layout range only defines the area that is depicted (i.e. the zoom)
for axis in layout.keys():
plot_layout["{0}2".format(axis)] = copy.copy(layout[axis])
plot_layout["xaxis2"]["autorange"] = False
plot_layout["xaxis2"]["range"] = [435.7, 437]
# Now the third plot will be added, a fragmentation spectrum of HLVDEPQNLIK
ms2_spectrum = run[3542]
# The MS_precision for the plotting option label.triangle.MS_precision
# needs to be defined
p.new_plot(title="MS2 Spectrum Annotated: HLVDEPQNLIK", MS_precision=5e-4)
p.add(
ms2_spectrum.peaks("centroided"),
color=(0, 0, 0),
opacity=1,
style="sticks",
name="raw data plot 3",
plot_num=2,
)
theoretical_b_ions = {
"b<sub>2</sub><sup>+2</sup>": 126.0788,
"b<sub>3</sub><sup>+2</sup>": 175.6130,
"b<sub>4</sub><sup>+2</sup>": 233.1264,
"b<sub>2</sub>": 251.1503,
"b<sub>5</sub><sup>+2</sup>": 297.6477,
"b<sub>6</sub><sup>+2</sup>": 346.1741,
"b<sub>3</sub>": 350.2187,
"b<sub>7</sub><sup>+2</sup>": 410.2034,
"b<sub>4</sub>": 465.2456,
"b<sub>8</sub><sup>+2</sup>": 467.2249,
"b<sub>9</sub><sup>+2</sup>": 523.7669,
"b<sub>10</sub><sup>+2</sup>": 580.3089,
"b<sub>5</sub>": 594.2882,
"b<sub>6</sub>": 691.341,
"b<sub>7</sub>": 819.3995,
"b<sub>8</sub>": 933.4425,
"b<sub>9</sub>": 1046.5265,
"b<sub>10</sub>": 1159.6106,
}
theoretical_y_ions = {
"y<sub>1</sub><sup>+2</sup>": 74.0600,
"y<sub>2</sub><sup>+2</sup>": 130.6021,
"y<sub>1</sub>": 147.1128,
"y<sub>3</sub><sup>+2</sup>": 187.1441,
"y<sub>4</sub><sup>+2</sup>": 244.1656,
"y<sub>2</sub>": 260.1969,
"y<sub>5</sub><sup>+2</sup>": 308.1949,
"y<sub>6</sub><sup>+2</sup>": 356.7212,
"y<sub>3</sub>": 373.2809,
"y<sub>7</sub><sup>+2</sup>": 421.2425,
"y<sub>8</sub><sup>+2</sup>": 478.7560,
"y<sub>4</sub>": 487.3239,
"y<sub>9</sub><sup>+2</sup>": 528.2902,
"y<sub>10</sub><sup>+2</sup>": 584.8322,
"y<sub>5</sub>": 615.3824,
"y<sub>6</sub>": 712.4352,
"y<sub>7</sub>": 841.4778,
"y<sub>8</sub>": 956.5047,
"y<sub>9</sub>": 1055.5732,
"y<sub>10</sub>": 1168.6572,
}
# Check which theoretical fragments are present in the spectrum
# using the has_peak() function
for ion_list in [theoretical_b_ions, theoretical_y_ions]:
label_list = []
for fragment in ion_list.keys():
peak = ms2_spectrum.has_peak(ion_list[fragment])
if len(peak) != 0:
label_list.append((ion_list[fragment], peak[0][1], fragment))
if ion_list == theoretical_b_ions:
color = (0, 0, 255)
else:
color = (0, 255, 0)
p.add(
label_list,
color=color,
style="label.triangle.MS_precision",
name="theoretical fragment ions plot 3",
)
for axis in layout.keys():
plot_layout["{0}3".format(axis)] = copy.copy(layout[axis])
# Save the plot in a file using the defined plot_layout
filename = "example_plot_{0}_annotation.html".format(os.path.basename(example_file))
p.save(filename=filename, layout=plot_layout)
print("Plotted file: {0}".format(filename))
if __name__ == "__main__":
main()
|