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Training dataset: DIA data analysis of a HEK/Ecoli Spike-in dataset using OpenSwathWorkflow

Vogele, Daniel; Stillger, Maren; Fahrner, Matthias; Schilling, Oliver


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    <dct:title>Training dataset: DIA data analysis of a HEK/Ecoli Spike-in dataset using OpenSwathWorkflow</dct:title>
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    <dct:description>&lt;p&gt;The eight&amp;nbsp;raw files serve as a concise but meaningful training data set in the Galaxy training network (https://galaxyproject.github.io/training-material/).&lt;/p&gt; &lt;p&gt;HEK and E.coli cell pellets were lysed with 5 % SDS, 50 mM triethylammonium bicarbonate (TEAB), pH 7.55. The obtained protein extracts were reduced by adding f.c. 5 mM TCEP and alkylated by the addition of f.c. 10 mM iodacetamide. Protein digestion and purification was performed on S-Trap columns. To ensure protein binding to the S-Trap columns, samples were acidified to a final concentration of 1.2 % phosphoric acid (~ pH 2). Six times the sample volume S-Trap buffer (90% aqueous methanol containing a final concentration of 100 mM TEAB, pH 7.1) was added to the samples which were then loaded on the columns and washed with S-Trap buffer. Protein digestion was performed with trypsin and LysC for one hour at 47 &amp;deg;C. Peptides were eluted in three steps with (1) 50 mM TEAB, (2) 0.2 % aqueous formic acid and (3) 50 % acetonitrile containing 0.2 % formic acid. Eluted peptides of HEK and E.coli were mixed in two different ratios and four replicates&amp;nbsp;of each Spike/in ratio were measured:&lt;/p&gt; &lt;p&gt;Sample&amp;nbsp;&amp;nbsp; &amp;nbsp;HEK&amp;nbsp;&amp;nbsp; &amp;nbsp;E.coli&amp;nbsp;&amp;nbsp; &amp;nbsp;MS method&lt;br&gt; Sample1&amp;nbsp;&amp;nbsp; &amp;nbsp;2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.15&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample2&amp;nbsp;&amp;nbsp; &amp;nbsp;2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.15&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample3&amp;nbsp;&amp;nbsp; &amp;nbsp;2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.15&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample4&amp;nbsp; &amp;nbsp; 2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.15&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample5&amp;nbsp;&amp;nbsp; &amp;nbsp;2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.80&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample6&amp;nbsp; &amp;nbsp; 2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.80&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample7&amp;nbsp; &amp;nbsp; 2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.80&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;br&gt; Sample8&amp;nbsp; &amp;nbsp; 2.5&amp;nbsp; &amp;nbsp; &amp;nbsp; 0.80&amp;nbsp; &amp;nbsp; &amp;nbsp; &amp;nbsp; DIA&lt;/p&gt; &lt;p&gt;Additionally, iRT peptides were added and 1&amp;micro;g of each samples&amp;nbsp;was measured using&amp;nbsp;data independent acquisition with a Q-Exactive Plus mass spectrometer. Briefly, a scan range from 400-1000 m/Z was first covered by an MS1 scan followed by 25 consecutive MS2 scans (each&amp;nbsp;24 m/z broad). In the next cycle another&amp;nbsp;MS1 scan was acquired followd by 26 MS2 scans (also 24m/z broad) in which the window centers were shifted by 50% compared to the previous cycle of MS2 scans. The resulting raw files contain overlapping MS2 scans.&lt;/p&gt; &lt;p&gt;Besides the eight raw files, we uploaded a spectral library, a&amp;nbsp;transition list for the iRT peptides as well as an sample annotation file.&lt;br&gt; Additionally, we uploaded&amp;nbsp;the Galaxy PyProphet score&amp;nbsp;training result files: PyProphet score report and PyProphet score.&lt;/p&gt;</dct:description>
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