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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        About MultiQC

        This report was generated using MultiQC, version 1.33

        Video: Using MultiQC Reports MultiQC homepage MultiQC documentation Source code Issue tracker

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        MultiQC is developed by Seqera.

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        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2026-01-22, 15:02 UTC based on data in: /home/runner/work/pmultiqc/pmultiqc/data_temp
        Because this report contains a lot of samples, you may need to click 'Show plot' to see some graphs.

        pmultiqc

        pmultiqc is a MultiQC module to show the pipeline performance of mass spectrometry based quantification pipelines such as nf-core/quantms, MaxQuant, DIA-NN, and FragPipe.https://github.com/bigbio/pmultiqc

        Results Overview

        Summary Table

        This table shows the summary statistics of the submitted data.
        This table shows the summary statistics of the submitted data.
        Showing 1/1 rows.
        #Peptides Quantified#Proteins Quantified
        8051
        2165

        HeatMap

        This heatmap provides an overview of the performance of the quantms DIA (DIA-NN) results.
        This plot shows the pipeline performance overview. Some metrics are calculated. *Heatmap score[Contaminants]: as fraction of summed intensity with 0 = sample full of contaminants; 1 = no contaminants *Heatmap score[Pep Intensity (>23.0)]: Linear scale of the median intensity reaching the threshold, i.e. reaching 2^21 of 2^23 gives score 0.25. *Heatmap score[Charge]: Deviation of the charge 2 proportion from a representative Raw file (median). For typtic digests, peptides of charge 2 (one N-terminal and one at tryptic C-terminal R or K residue) should be dominant. Ionization issues (voltage?), in-source fragmentation, missed cleavages and buffer irregularities can cause a shift (see Bittremieux 2017, DOI: 10.1002/mas.21544) *Heatmap score[RT Alignment]: Compute 1 minus the mean absolute difference between 'RT' and 'Predicted.RT', and take the maximum of this value and 0. 1: |RT - Predicted.RT| = 0 *Heatmap score [ID rate over RT]: Judge column occupancy over retention time. Ideally, the LC gradient is chosen such that the number of identifications (here, after FDR filtering) is uniform over time, to ensure consistent instrument duty cycles. Sharp peaks and uneven distribution of identifications over time indicate potential for LC gradient optimization.Scored using 'Uniform' scoring function. i.e. constant receives good score, extreme shapes are bad *Heatmap score [Norm Factor]: Computes the mean absolute deviation (MAD) of 'Normalisation.Factor' from its mean. 0 = high variability in normalization factors; 1 = perfectly consistent normalization factors *Heatmap score [Peak Width]: Average peak width (RT.Stop - RT.Start). 1 = peak width equals 0; 0 = peak width equals 1 or greater
        Created with MultiQC

        Pipeline Result Statistics

        This plot shows the final pipeline results.
        Including Sample Name, Possible Study Variables, identified the number of peptide in the pipeline, and identified the number of modified peptide in the pipeline, eg. All data in this table are obtained from the out_msstats file. You can also remove the decoy with the `remove_decoy` parameter. In the FragPipe results summary, the data were obtained from psm.tsv.
        Showing 158/158 rows and 4/4 columns.
        Sample Name#Peptide IDs#Unambiguous Peptide IDs#Modified Peptide IDs#Protein (group) IDs
        20230626_KK_SC_IFNy_01_A7_1_14074
        1422
        1193
        0
        580
        20230626_KK_SC_IFNy_02_B7_1_14075
        1462
        1236
        0
        592
        20230626_KK_SC_IFNy_03_C7_1_14076
        1374
        1154
        0
        553
        20230626_KK_SC_IFNy_04_D7_1_14077
        2094
        1809
        0
        786
        20230626_KK_SC_IFNy_05_E7_1_14078
        1635
        1376
        0
        604
        20230626_KK_SC_IFNy_06_F7_1_14079
        1824
        1576
        0
        664
        20230626_KK_SC_IFNy_07_G7_1_14080
        2397
        2106
        0
        859
        20230626_KK_SC_IFNy_09_A8_1_14083
        1623
        1380
        0
        595
        20230626_KK_SC_IFNy_10_B8_1_14084
        1580
        1352
        0
        600
        20230626_KK_SC_IFNy_11_A6_1_14089
        1353
        1151
        0
        584
        20230626_KK_SC_IFNy_12_B6_1_14090
        1559
        1318
        0
        634
        20230626_KK_SC_IFNy_13_C6_1_14091
        1447
        1239
        0
        590
        20230626_KK_SC_IFNy_14_D6_1_14092
        1554
        1323
        0
        646
        20230626_KK_SC_IFNy_15_E6_1_14093
        1584
        1329
        0
        645
        20230626_KK_SC_IFNy_16_F6_1_14094
        1917
        1646
        0
        754
        20230626_KK_SC_IFNy_17_G6_1_14095
        1949
        1669
        0
        700
        20230626_KK_SC_IFNy_19_A7_1_14107
        2610
        2298
        0
        902
        20230626_KK_SC_IFNy_20_B7_1_14108
        1911
        1638
        0
        734
        20230626_KK_SC_IFNy_21_C7_1_14109
        1933
        1667
        0
        763
        20230626_KK_SC_IFNy_22_D7_1_14110
        1562
        1332
        0
        621
        20230626_KK_SC_IFNy_23_E7_1_14111
        1320
        1106
        0
        545
        20230626_KK_SC_IFNy_24_F7_1_14112
        1851
        1584
        0
        712
        20230626_KK_SC_IFNy_25_G7_1_14113
        1165
        965
        0
        494
        20230626_KK_SC_IFNy_27_A8_1_14125
        2032
        1759
        0
        755
        20230626_KK_SC_IFNy_28_B8_1_14126
        1353
        1135
        0
        583
        20230626_KK_SC_IFNy_29_C8_1_14127
        1486
        1260
        0
        631
        20230626_KK_SC_IFNy_30_D8_1_14128
        1484
        1254
        0
        584
        20230626_KK_SC_IFNy_31_E8_1_14129
        1190
        1006
        0
        537
        20230626_KK_SC_IFNy_32_F8_1_14130
        1321
        1109
        0
        581
        20230626_KK_SC_IFNy_33_G8_1_14131
        1158
        973
        0
        508
        20230626_KK_SC_IFNy_35_A9_1_14143
        2298
        2009
        0
        765
        20230626_KK_SC_IFNy_36_B9_1_14144
        1551
        1335
        0
        609
        20230626_KK_SC_IFNy_37_C9_1_14145
        1825
        1584
        0
        721
        20230626_KK_SC_IFNy_38_D9_1_14146
        2343
        2043
        0
        883
        20230626_KK_SC_IFNy_39_E9_1_14147
        1027
        860
        0
        421
        20230626_KK_SC_IFNy_40_F9_1_14148
        2170
        1865
        0
        780
        20230626_KK_SC_IFNy_41_G9_1_14149
        1472
        1255
        0
        597
        20230626_KK_SC_IFNy_42_H9_1_14150
        1444
        1231
        0
        577
        20230626_KK_SC_IFNy_43_A10_1_14161
        1414
        1199
        0
        611
        20230626_KK_SC_IFNy_44_B10_1_14162
        1714
        1478
        0
        681
        20230626_KK_SC_IFNy_45_C10_1_14163
        1570
        1337
        0
        629
        20230626_KK_SC_IFNy_46_D10_1_14164
        2141
        1853
        0
        802
        20230626_KK_SC_IFNy_47_E10_1_14165
        1558
        1342
        0
        619
        20230626_KK_SC_IFNy_49_G10_1_14167
        1171
        980
        0
        498
        20230626_KK_SC_control_01_A6_1_14065
        1909
        1650
        0
        769
        20230626_KK_SC_control_02_B6_1_14066
        2615
        2278
        0
        926
        20230626_KK_SC_control_03_C6_1_14067
        1505
        1268
        0
        630
        20230626_KK_SC_control_04_D6_1_14068
        538
        429
        0
        252
        20230626_KK_SC_control_05_E6_1_14069
        1655
        1425
        0
        647
        20230626_KK_SC_control_06_F6_1_14070
        1660
        1421
        0
        636
        20230626_KK_SC_control_07_G6_1_14071
        3834
        3363
        0
        1119
        20230626_KK_SC_control_09_A5_1_14086
        593
        481
        0
        275
        20230626_KK_SC_control_10_B5_1_14087
        600
        471
        0
        258
        20230626_KK_SC_control_11_A5_1_14098
        1696
        1449
        0
        659
        20230626_KK_SC_control_12_B5_1_14099
        1756
        1490
        0
        690
        20230626_KK_SC_control_13_C5_1_14100
        1564
        1351
        0
        626
        20230626_KK_SC_control_14_D5_1_14101
        1802
        1552
        0
        706
        20230626_KK_SC_control_15_E5_1_14102
        1437
        1229
        0
        582
        20230626_KK_SC_control_16_F5_1_14103
        1519
        1310
        0
        623
        20230626_KK_SC_control_17_G5_1_14104
        1402
        1180
        0
        566
        20230626_KK_SC_control_19_A4_1_14116
        1515
        1305
        0
        597
        20230626_KK_SC_control_20_B4_1_14117
        1878
        1669
        0
        723
        20230626_KK_SC_control_21_C4_1_14118
        2701
        2358
        0
        904
        20230626_KK_SC_control_22_D4_1_14119
        1818
        1581
        0
        700
        20230626_KK_SC_control_23_E4_1_14120
        2064
        1778
        0
        733
        20230626_KK_SC_control_24_F4_1_14121
        1779
        1536
        0
        705
        20230626_KK_SC_control_25_G4_1_14122
        1330
        1121
        0
        577
        20230626_KK_SC_control_26_H4_1_14123
        1696
        1462
        0
        662
        20230626_KK_SC_control_28_B3_1_14135
        2398
        2072
        0
        856
        20230626_KK_SC_control_29_C3_1_14136
        2220
        1944
        0
        807
        20230626_KK_SC_control_30_D3_1_14137
        1929
        1655
        0
        721
        20230626_KK_SC_control_31_E3_1_14138
        1560
        1329
        0
        612
        20230626_KK_SC_control_32_F3_1_14139
        1216
        1029
        0
        538
        20230626_KK_SC_control_33_G3_1_14140
        2314
        2010
        0
        859
        20230626_KK_SC_control_35_A2_1_14152
        1948
        1689
        0
        766
        20230626_KK_SC_control_36_B2_1_14153
        2077
        1803
        0
        783
        20230626_KK_SC_control_37_C2_1_14154
        4058
        3580
        0
        1247
        20230626_KK_SC_control_38_D2_1_14155
        778
        653
        0
        285
        20230626_KK_SC_control_39_E2_1_14156
        1138
        946
        0
        506
        20230626_KK_SC_control_40_F2_1_14157
        1318
        1089
        0
        538
        20230626_KK_SC_control_41_G2_1_14158
        1474
        1256
        0
        600
        20230626_KK_SC_control_43_A1_1_14170
        4587
        4048
        0
        1257
        20230626_KK_SC_control_44_B1_1_14171
        2147
        1864
        0
        776
        20230626_KK_SC_control_45_C1_1_14172
        1252
        1053
        0
        543
        20230626_KK_SC_control_46_D1_1_14173
        1918
        1670
        0
        722
        20230626_KK_SC_control_47_E1_1_14174
        1913
        1649
        0
        729
        20230626_KK_SC_control_48_F1_1_14175
        1695
        1452
        0
        678
        20230626_KK_SC_control_49_G1_1_14176
        937
        785
        0
        399
        20230629_KK_10SC_IFNy_01_A12_1_14179
        3361
        2986
        0
        1118
        20230629_KK_10SC_IFNy_02_B12_1_14180
        3233
        2883
        0
        1078
        20230629_KK_10SC_IFNy_03_C12_1_14182
        4311
        3850
        0
        1353
        20230629_KK_10SC_IFNy_04_D12_1_14183
        5794
        5156
        0
        1523
        20230629_KK_10SC_IFNy_05_E12_1_14191
        5611
        5008
        0
        1510
        20230629_KK_10SC_IFNy_06_F12_1_14192
        5881
        5282
        0
        1563
        20230629_KK_10SC_IFNy_07_G12_1_14194
        5602
        5003
        0
        1469
        20230629_KK_10SC_control_01_A11_1_14185
        3310
        2938
        0
        1136
        20230629_KK_10SC_control_02_B11_1_14186
        3162
        2797
        0
        1082
        20230629_KK_10SC_control_03_C11_1_14188
        3086
        2748
        0
        1064
        20230629_KK_10SC_control_04_D11_1_14189
        3401
        3030
        0
        1125
        20230629_KK_10SC_control_05_E11_1_14197
        2990
        2669
        0
        1037
        20230629_KK_10SC_control_06_F11_1_14198
        3351
        2977
        0
        1112
        20230629_KK_10SC_control_07_G11_1_14200
        3773
        3357
        0
        1237
        20230629_KK_10SC_control_08_H11_1_14201
        4121
        3581
        0
        1148
        20230630_KK_SC_IFNy_51_A7_1_14204
        1543
        1321
        0
        632
        20230630_KK_SC_IFNy_52_B7_1_14205
        1697
        1436
        0
        683
        20230630_KK_SC_IFNy_53_C7_1_14206
        1766
        1495
        0
        693
        20230630_KK_SC_IFNy_54_D7_1_14207
        1434
        1224
        0
        594
        20230630_KK_SC_IFNy_55_E7_1_14208
        1500
        1286
        0
        626
        20230630_KK_SC_IFNy_56_F7_1_14209
        903
        741
        0
        392
        20230630_KK_SC_IFNy_57_G7_1_14210
        977
        804
        0
        432
        20230630_KK_SC_IFNy_58_H7_1_14211
        834
        689
        0
        384
        20230630_KK_SC_IFNy_59_A8_1_14222
        796
        643
        0
        365
        20230630_KK_SC_IFNy_60_B8_1_14223
        1812
        1552
        0
        699
        20230630_KK_SC_IFNy_61_C8_1_14224
        1860
        1618
        0
        727
        20230630_KK_SC_IFNy_62_D8_1_14225
        1565
        1338
        0
        659
        20230630_KK_SC_IFNy_63_E8_1_14226
        2674
        2349
        0
        934
        20230630_KK_SC_IFNy_64_F8_1_14227
        2062
        1791
        0
        763
        20230630_KK_SC_IFNy_65_G8_1_14228
        920
        754
        0
        393
        20230630_KK_SC_IFNy_67_A9_1_14240
        1618
        1384
        0
        651
        20230630_KK_SC_IFNy_68_B9_1_14241
        1967
        1681
        0
        775
        20230630_KK_SC_IFNy_69_C9_1_14242
        1702
        1479
        0
        692
        20230630_KK_SC_IFNy_70_D9_1_14243
        1604
        1378
        0
        650
        20230630_KK_SC_IFNy_71_E9_1_14244
        1589
        1367
        0
        657
        20230630_KK_SC_IFNy_72_F9_1_14245
        862
        703
        0
        381
        20230630_KK_SC_IFNy_73_G9_1_14246
        516
        417
        0
        252
        20230630_KK_SC_IFNy_75_A10_1_14258
        1156
        977
        0
        475
        20230630_KK_SC_IFNy_76_B10_1_14259
        818
        674
        0
        351
        20230630_KK_SC_IFNy_77_C10_1_14260
        2372
        2078
        0
        852
        20230630_KK_SC_IFNy_78_D10_1_14261
        733
        607
        0
        331
        20230630_KK_SC_IFNy_79_E10_1_14262
        1058
        894
        0
        453
        20230630_KK_SC_IFNy_81_G10_1_14264
        1419
        1201
        0
        568
        20230630_KK_SC_control_51_A6_1_14213
        1789
        1530
        0
        701
        20230630_KK_SC_control_52_B6_1_14214
        1458
        1234
        0
        601
        20230630_KK_SC_control_53_C6_1_14215
        2108
        1828
        0
        838
        20230630_KK_SC_control_54_D6_1_14216
        2075
        1792
        0
        792
        20230630_KK_SC_control_56_F6_1_14218
        1233
        1040
        0
        523
        20230630_KK_SC_control_58_H6_1_14220
        1598
        1360
        0
        665
        20230630_KK_SC_control_59_A5_1_14231
        1649
        1406
        0
        669
        20230630_KK_SC_control_60_B5_1_14232
        777
        643
        0
        340
        20230630_KK_SC_control_61_C5_1_14233
        1697
        1451
        0
        689
        20230630_KK_SC_control_62_D5_1_14234
        2115
        1830
        0
        783
        20230630_KK_SC_control_63_E5_1_14235
        819
        683
        0
        350
        20230630_KK_SC_control_64_F5_1_14236
        1400
        1155
        0
        584
        20230630_KK_SC_control_65_G5_1_14237
        603
        492
        0
        277
        20230630_KK_SC_control_67_A4_1_14249
        1794
        1551
        0
        697
        20230630_KK_SC_control_68_B4_1_14250
        1948
        1701
        0
        724
        20230630_KK_SC_control_69_C4_1_14251
        2150
        1841
        0
        821
        20230630_KK_SC_control_70_D4_1_14252
        1105
        918
        0
        479
        20230630_KK_SC_control_71_E4_1_14253
        691
        564
        0
        302
        20230630_KK_SC_control_72_F4_1_14254
        624
        512
        0
        277
        20230630_KK_SC_control_73_G4_1_14255
        1571
        1349
        0
        613
        20230630_KK_SC_control_75_A3_1_14267
        1289
        1103
        0
        520
        20230630_KK_SC_control_76_B3_1_14268
        1556
        1329
        0
        619
        20230630_KK_SC_control_77_C3_1_14269
        1556
        1342
        0
        633
        20230630_KK_SC_control_78_D3_1_14270
        1786
        1544
        0
        702
        20230630_KK_SC_control_79_E3_1_14271
        1615
        1386
        0
        633
        20230630_KK_SC_control_80_A10_1_14272
        1302
        1096
        0
        573
        20230630_KK_SC_control_82_C10_1_14274
        1890
        1641
        0
        732
        Expand table

        Identification Summary

        Number of Peptides identified Per Protein

        This plot shows the number of peptides per protein in quantms pipeline final result
        This statistic is extracted from the out_msstats file. Proteins supported by more peptide identifications can constitute more confident results.
        Created with MultiQC

        ProteinGroups Count

        Number of protein groups per raw file.
        Based on statistics calculated from mzTab, mzIdentML (mzid), DIA-NN report files, or FragPipe psm.tsv.
        Created with MultiQC

        Peptide ID Count

        Number of unique (i.e. not counted twice) peptide sequences including modifications per Raw file.
        Based on statistics calculated from mzTab, mzIdentML (mzid), DIA-NN report files, or FragPipe psm.tsv.
        Created with MultiQC

        Peptide Length Distribution

        Peptide length distribution per Run.
        Peptide length distribution.
        FragPipe: psm.tsv ('Peptide Length': number of residues in the peptide sequence).
        MaxQuant: evidence.txt ('Length': the length of the sequence stored in the column 'Sequence').
        DIA-NN: report.tsv (the length of the 'Stripped.Sequence').
        quantms: *.mzTab (the length of sequence).
        Created with MultiQC

        Quantification Analysis

        Peptides Quantification Table

        This plot shows the quantification information of peptides in the final result (DIA-NN report).
        The quantification information of peptides is obtained from the DIA-NN output file. The table shows the quantitative level and distribution of peptides in different study variables, run and peptiforms. The distribution show all the intensity values in a bar plot above and below the average intensity for all the fractions, runs and peptiforms. * BestSearchScore: It is equal to min(1 - Q.Value) for DIA-NN datasets. * Average Intensity: Average intensity of each peptide sequence across all conditions (0 or NA ignored). * Peptide intensity in each condition (Eg. `CT=Mixture;CN=UPS1;QY=0.1fmol`).
        Showing 50/50 rows and 4/4 columns.
        PeptideIDProtein NamePeptide SequenceBest Search ScoreAverage Intensity
        1
        RL4_HUMAN
        AAAAAAALQAK
        0.9902
        2.6246
        2
        FUMH_HUMAN
        AAAEVNQDYGLDPK
        0.9901
        2.5643
        3
        TOM70_HUMAN
        AAAFEQLQK
        0.9901
        2.6455
        4
        PLEC_HUMAN
        AAAGKAELELELGR
        0.9901
        2.5892
        5
        RUFY1_HUMAN
        AAAGLGGGDSGDGTAR
        0.9997
        2.5814
        6
        MIC19_HUMAN
        AAANEQLTR
        0.9901
        2.7989
        7
        ODPA_HUMAN
        AAASTDYYK
        0.9915
        2.5269
        8
        ODPA_HUMAN
        AAASTDYYKR
        0.9910
        2.2373
        9
        NDUV2_HUMAN
        AAAVLPVLDLAQR
        0.9901
        2.5184
        10
        TPM3_HUMAN
        AADAEAEVASLNR
        0.9912
        2.5851
        11
        SNW1_HUMAN
        AADKLAPAQYIR
        0.9924
        2.3333
        12
        S10AG_HUMAN
        AADKLIQNLDANHDGR
        0.9906
        2.4694
        13
        EVPL_HUMAN
        AAEDAVYELQSK
        0.9970
        2.6177
        14
        PHB_HUMAN
        AAELIANSLATAGDGLIELR
        0.9900
        2.5985
        15
        TREX2_HUMAN
        AAELLAWADEQAR
        0.9996
        2.6645
        16
        LMAN1_HUMAN
        AAFENWEVEVTFR
        0.9938
        2.4284
        17
        K22E_HUMAN
        AAFGGSGGR
        0.9909
        4.1891
        18
        SRRM2_HUMAN
        AAFGISDSYVDGSSFDPQRR
        0.9916
        2.5985
        19
        ALDH2_HUMAN
        AAFQLGSPWR
        0.9918
        2.6380
        20
        SPEE_HUMAN
        AAFVLPEFAR
        0.9913
        2.5888
        21
        ITA3_HUMAN
        AAFVSEQQQK
        0.9908
        3.0893
        22
        TACD2_HUMAN
        AAGDVDIGDAAYYFER
        0.9913
        2.3003
        23
        PIGR_HUMAN
        AAGSRDVSLAK
        0.9994
        2.9501
        24
        JAGN1_HUMAN
        AAGTDGSDFQHR
        0.9938
        1.7763
        25
        JAGN1_HUMAN
        AAGTDGSDFQHRER
        0.9911
        2.4834
        26
        RLA1_HUMAN
        AAGVNVEPFWPGLFAK
        0.9964
        3.0044
        27
        TCPB_HUMAN
        AAHSEGNTTAGLDMR
        0.9906
        2.6088
        28
        PHB_HUMAN
        AAIISAEGDSK
        0.9925
        3.1291
        29
        PHB_HUMAN
        AAIISAEGDSKAAELIANSLATAGDGLIELR
        0.9906
        2.3424
        30
        MYH14_HUMAN
        AAILEEKR
        0.9902
        2.5634
        31
        NTF2_HUMAN
        AAIVEKLSSLPFQK
        0.9918
        2.3449
        32
        EMAL4_HUMAN
        AALADVLR
        0.9994
        2.7906
        33
        EMAL4_HUMAN
        AALADVLRR
        0.9994
        2.3608
        34
        PLEC_HUMAN
        AALAHSEEVTASQVAATK
        0.9900
        2.7791
        35
        EVPL_HUMAN
        AALDLER
        0.9986
        2.8679
        36
        TBL3_HUMAN
        AALEALLPYTER
        0.9903
        2.5478
        37
        SIPA1_HUMAN
        AALEEEVR
        0.9935
        2.5965
        38
        PLEC_HUMAN
        AALEEVERLK
        0.9926
        2.6259
        39
        K1C9_HUMAN
        AALEKSLEDTK
        0.9910
        2.6091
        40
        HMOX1_HUMAN
        AALEQDLAFWYGPR
        0.9955
        2.8445
        41
        PXL2A_HUMAN
        AALEYLEDIDLK
        0.9918
        2.1066
        42
        SP16H_HUMAN
        AALLTER
        0.9908
        2.5853
        43
        RS25_HUMAN
        AALQELLSK
        0.9908
        2.6922
        44
        ECHB_HUMAN
        AALTGLLHR
        0.9909
        3.2359
        45
        LXN_HUMAN
        AALVAQNYINYQQGTPHR
        0.9907
        2.5402
        46
        TBB6_HUMAN
        AALVDLEPGTMDSVR
        0.9982
        2.8610
        47
        PGM2_HUMAN
        AAMGPGISR
        0.9940
        2.7615
        48
        PLAK_HUMAN
        AAMIVNQLSK
        0.9942
        3.4678
        49
        PLAK_HUMAN
        AAMIVNQLSKK
        0.9951
        3.0329
        50
        ANXA1_HUMAN
        AAMKGLGTDEDTLIEILASR
        0.9941
        2.9676
        Expand table

        Protein Quantification Table

        This plot shows the quantification information of proteins in the final result (DIA-NN report).
        The quantification information of proteins is obtained from the DIA-NN output file. The table shows the quantitative level and distribution of proteins in different study variables and run. * Peptides_Number: The number of peptides for each protein. * Average Intensity: Average intensity of each protein across all conditions (0 or NA ignored). * Protein intensity in each condition (Eg. `CT=Mixture;CN=UPS1;QY=0.1fmol`): Summarize intensity of peptides.
        Showing 50/50 rows and 3/3 columns.
        ProteinIDProtein NameNumber of PeptidesAverage Intensity
        1
        1433B_HUMAN
        3
        2.4811
        2
        1433B_HUMAN;1433E_HUMAN;1433G_HUMAN;1433S_HUMAN;1433T_HUMAN;1433Z_HUMAN
        1
        3.1921
        3
        1433B_HUMAN;1433G_HUMAN;1433Z_HUMAN
        1
        2.3877
        4
        1433B_HUMAN;1433S_HUMAN;1433T_HUMAN;1433Z_HUMAN
        1
        2.9864
        5
        1433B_HUMAN;1433T_HUMAN
        1
        3.0819
        6
        1433B_HUMAN;1433T_HUMAN;1433Z_HUMAN
        1
        3.0938
        7
        1433E_HUMAN
        3
        2.6973
        8
        1433G_HUMAN
        2
        2.5469
        9
        1433G_HUMAN;1433S_HUMAN;1433Z_HUMAN
        1
        3.9055
        10
        1433S_HUMAN
        10
        3.0845
        11
        1433Z_HUMAN
        7
        2.8169
        12
        2AAA_HUMAN
        4
        2.5865
        13
        4F2_HUMAN
        11
        2.7064
        14
        5NT3A_HUMAN
        2
        2.4555
        15
        5NT3B_HUMAN
        1
        3.0432
        16
        6PGD_HUMAN
        6
        2.8426
        17
        6PGL_HUMAN
        4
        2.6621
        18
        A1AT_HUMAN
        3
        2.6320
        19
        A2GL_HUMAN
        1
        2.2294
        20
        A2MG_HUMAN
        4
        2.4513
        21
        A2ML1_HUMAN
        21
        2.9154
        22
        AAAT_HUMAN
        2
        2.6901
        23
        AACT_HUMAN
        4
        2.4266
        24
        AAMP_HUMAN
        1
        2.9336
        25
        AASS_HUMAN
        1
        2.4655
        26
        AATC_HUMAN
        9
        2.7361
        27
        AATM_HUMAN
        10
        2.8109
        28
        ABCA7_HUMAN
        1
        3.2719
        29
        ABCB5_HUMAN
        1
        3.8196
        30
        ABHD1_HUMAN
        1
        2.7882
        31
        ABHDA_HUMAN
        2
        2.4077
        32
        ABHDB_HUMAN
        1
        2.4833
        33
        ABHEB_HUMAN
        1
        2.2487
        34
        ABHGA_HUMAN
        1
        2.0888
        35
        ABI1_HUMAN
        1
        2.5522
        36
        ABL2_HUMAN
        1
        3.3552
        37
        ABLM1_HUMAN
        1
        2.6041
        38
        ACACA_HUMAN
        1
        2.8701
        39
        ACAD9_HUMAN
        2
        2.4690
        40
        ACADM_HUMAN
        4
        2.4907
        41
        ACADS_HUMAN
        1
        2.3229
        42
        ACADV_HUMAN
        8
        2.6504
        43
        ACBP_HUMAN
        2
        3.0188
        44
        ACE_HUMAN
        1
        3.4431
        45
        ACINU_HUMAN
        2
        2.5839
        46
        ACON_HUMAN
        8
        2.7587
        47
        ACOT1_HUMAN
        1
        2.7624
        48
        ACOT1_HUMAN;ACOT2_HUMAN
        2
        2.7421
        49
        ACOT2_HUMAN
        1
        3.0597
        50
        ACOT9_HUMAN
        1
        2.4193
        Expand table

        Intensity Distribution

        log2(Precursor.Quantity) for each Run (or Sample).
        [DIA-NN: main report] log2(Precursor.Quantity) for each Run (or Sample).

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

        Standard Deviation of Intensity

        Standard deviation of intensity by sample (experimental conditions).
        [DIA-NN: report.tsv] Sample grouping is derived from the SDRF when available; otherwise, it is parsed from "Run" names. First, identify the experimental conditions from the "Run" name. Then, group the data by experimental condition and Modified.Sequence, and calculate the standard deviation of log2(Precursor.Quantity).
        Created with MultiQC

        MS1 Analysis

        MS1 Area Distribution

        log2(Ms1.Area) for each Run.
        [DIA-NN: report.tsv] log2(Ms1.Area) for each Run. Ms1.Area: non-normalised MS1 peak area.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).

        MS2 and Spectral Stats

        Distribution of Precursor Charges

        This is a bar chart representing the distribution of the precursor ion charges for a given whole experiment.
        [DIA-NN: main report] distribution of the precursor ion charges for a given whole experiment. Precursor.Charge: the charge of the precursor.
        Created with MultiQC

        Charge-state

        The distribution of the charge-state of the precursor ion.
        [DIA-NN: main report] The distribution of the charge-state of the precursor ion (Precursor.Charge).
        Created with MultiQC

        RT Quality Control

        IDs over RT

        Distribution of retention time, derived from the main report.
        [DIA-NN: main report] Distribution of retention time (RT) for each run.

        This plot allows to judge column occupancy over retention time. Ideally, the LC gradient is chosen such that the number of identifications (here, after FDR filtering) is uniform over time, to ensure consistent instrument duty cycles. Sharp peaks and uneven distribution of identifications over time indicate potential for LC gradient optimization. See [Moruz 2014, DOI: 10.1002/pmic.201400036](https://pubmed.ncbi.nlm.nih.gov/24700534/) for details.

        Created with MultiQC

        Normalisation Factor over RT

        Distribution of Normalisation.Factor with retention time, derived from the main report.
        [DIA-NN: main report] Distribution of Normalisation.Factor with retention time (RT) for each run. RT: the retention time (RT) of the PSM in minutes. Normalisation.Factor: normalisation factor applied to the precursor in the specific run, i.e. normalised quantity = normalisation factor X non-normalised quantity
        Created with MultiQC

        Peak Width over RT

        Distribution of peak width with retention time, derived from the main report. Peak Width = RT.Stop - RT.Start.
        [DIA-NN: main report] Distribution of peak width with retention time (RT) for each run. RT: the retention time (RT) of the PSM in minutes. RT.Start and RT.Stop: peak boundaries.
        Created with MultiQC

        Absolute RT Error over RT

        Distribution of rt error with retention time, derived from the main report.
        [DIA-NN: main report] Distribution of absolute RT error (|RT - Predicted.RT|) with retention time (RT) for each run. RT: the retention time (RT) of the PSM in minutes. Predicted.RT: predicted RT based on the iRT.
        Created with MultiQC

        LOESS RT ~ iRT

        Distribution of LOESS RT ~ iRT for each run, derived from the main report.
        [DIA-NN: main report] Distribution of LOESS RT ~ iRT for each run. RT: the retention time (RT) of the PSM in minutes. iRT: reference RT as recorded in the spectral library.
        Created with MultiQC

        MultiQC v1.33 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.