Error in .mergeAnnotation(input, annotation) : ** Please check the annotation file. The channel name must be matched with that in input data.
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Tobias Kockmann
Jul 1, 2021, 7:04:03 AM7/1/21
to MSstats
Hi MSstatsTMT dev team,
I get the following error:
> input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, verbose = TRUE)
INFO [2021-06-30 17:03:52] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-06-30 17:03:55] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-06-30 17:03:55] ** Using provided annotation.
INFO [2021-06-30 17:03:55] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-06-30 17:03:55] ** The following options are used:
- Features will be defined by the columns: PeptideSequence, PrecursorCharge
- Shared peptides will be removed.
- Proteins with single feature will not be removed.
- Features with less than 3 measurements within each run will be removed.
INFO [2021-06-30 17:03:55] ** Features with all missing measurements across channels within each run are removed.
INFO [2021-06-30 17:03:55] ** Shared peptides are removed.
INFO [2021-06-30 17:03:55] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-06-30 17:03:55] ** PSMs have been aggregated to peptide ions.
Error in .mergeAnnotation(input, annotation) :
** Please check the annotation file. The channel name must be matched with that in input data.
But as far as I can judge they are matched:
> str(raw.pd)
'data.frame': 79949 obs. of 42 variables:
$ PSMs.Workflow.ID : int -130 -130 -130 -130 -130 -130 -130 -130 -130 -130 ...
$ PSMs.Peptide.ID : int 190 2468088 4196087 4195766 4195756 4195603 2468222 4195485 4195296 2468382 ...
$ Checked : chr "False" "False" "False" "False" ...
$ Confidence : chr "High" "High" "High" "High" ...
$ Identifying.Node : chr "Sequest HT (A2)" "Sequest HT (A2)" "Sequest HT (A2)" "Sequest HT (A2)" ...
$ PSM.Ambiguity : chr "Unambiguous" "Unambiguous" "Unambiguous" "Unambiguous" ...
$ Annotated.Sequence : chr "[M].sSGAHGEEGSAR.[M]" "[R].LQAGEETASHYR.[M]" "[R].EmEENFALEAANYQDTIGR.[L]" "[R].LLLNNDNLLR.[E]" ...
$ Modifications : chr "N-Term(TMT6plex)" "" "M2(Oxidation)" "" ...
$ Number.of.Proteins : int 2 1 2 6 1 4 3 1 2 2 ...
$ Master.Protein.Accessions : chr "P43024" "Q9Z0E0" "P20152" "A0A0N4SVM0" ...
$ Protein.Accessions : chr "P43024; Q9DCW5" "Q9Z0E0" "A0A0A6YWC8; P20152" "P47753; Q5RKN9; A0A0N4SVM0; P47754; D6RCW7; A0A0G2JE27" ...
$ Number.of.Missed.Cleavages : int 0 0 0 0 0 0 0 0 0 0 ...
$ Charge : int 3 3 2 2 2 2 2 3 2 3 ...
$ Delta.Score : num 0.708 0.609 0.815 0.468 0.67 ...
$ Delta.Cn : num 0 0 0 0 0 0 0 0 0 0 ...
$ Rank : int 1 1 1 1 1 1 1 1 1 1 ...
$ Search.Engine.Rank : int 1 1 1 1 1 1 1 1 1 1 ...
$ mz.in.Da : num 459 455 1109 599 611 ...
$ MHplus.in.Da : num 1374 1362 2217 1198 1222 ...
$ Theo.MHplus.in.Da : num 1374 1362 2217 1198 1222 ...
$ Delta.M.in.ppm : num 1.59 -0.3 0.84 0.2 0.21 0.09 -0.23 -0.16 0.37 0.73 ...
$ Delta.mz.in.Da : num 0.00073 -0.00013 0.00093 0.00012 0.00013 0.00005 -0.00011 -0.0001 0.00025 0.0007 ...
$ Activation.Type : chr "HCD" "HCD" "HCD" "HCD" ...
$ MS.Order : chr "MS2" "MS2" "MS2" "MS2" ...
$ Isolation.Interference.in.Percent: num 1.9 19.2 0 11.2 18.3 ...
$ Average.Reporter.SN : num 128.4 33 NA 3.3 1.6 ...
$ Ion.Inject.Time.in.ms : num 97.1 105 105 105 105 ...
$ RT.in.min : num 13.9 26.1 75.3 75.2 75.2 ...
$ First.Scan : int 2136 6737 27027 26968 26967 26923 6757 26903 26849 6783 ...
$ Spectrum.File : chr "20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw" "20200703_027_S219787_TMT-TAILS6plex_set3_pre_2.raw" "20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw" "20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw" ...
$ File.ID : chr "F1.4" "F2.2" "F3.3" "F3.3" ...
$ Abundance.126 : num 104.8 23.9 NA 2.5 2.7 ...
$ Abundance.127 : num 129.1 33.4 NA NA NA ...
$ Abundance.128 : num 116 22.7 NA 3.4 NA 8.8 23.9 34.2 9.6 27.1 ...
$ Abundance.129 : num 154.2 37 NA 5.9 NA ...
$ Abundance.130 : num 109.9 26.4 NA 5 2.5 ...
$ Abundance.131 : num 156.4 54.3 NA 2.8 4.5 ...
$ Quan.Info : chr "" "NoQuanLabels" "NoQuanLabels" "NoQuanLabels" ...
$ XCorr : num 4.04 2.84 4.6 1.86 1.88 1.68 2.35 3.39 1.33 3.68 ...
$ Number.of.Protein.Groups : int 1 1 1 1 1 1 1 1 1 1 ...
$ Percolator.q.Value : num 2.12e-05 2.12e-05 2.12e-05 2.12e-05 2.12e-05 ...
$ Percolator.PEP : num 1.04e-08 5.56e-04 5.25e-09 3.90e-05 6.26e-04 ...
>
> sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows Server 2012 R2 x64 (build 9600)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_1.0.6 tidyr_1.1.3 MSstatsTMT_2.0.1
loaded via a namespace (and not attached):
[1] MSstats_4.0.1 gtools_3.8.2 tidyselect_1.1.1 purrr_0.3.4
[5] splines_4.1.0 lmerTest_3.1-3 lattice_0.20-44 log4r_0.3.2
[9] colorspace_2.0-2 vctrs_0.3.8 generics_0.1.0 utf8_1.2.1
[13] survival_3.2-11 marray_1.70.0 rlang_0.4.11 nloptr_1.2.2.2
[17] pillar_1.6.1 glue_1.4.2 DBI_1.1.1 lifecycle_1.0.0
[21] munsell_0.5.0 gtable_0.3.0 caTools_1.18.2 fansi_0.5.0
[25] preprocessCore_1.54.0 Rcpp_1.0.6 KernSmooth_2.23-20 scales_1.1.1
[29] backports_1.2.1 checkmate_2.0.0 limma_3.48.1 lme4_1.1-27.1
[33] gplots_3.1.1 ggplot2_3.3.3 stringi_1.6.2 ggrepel_0.9.1
[37] numDeriv_2016.8-1.1 grid_4.1.0 MSstatsConvert_1.2.2 cli_2.5.0
[41] tools_4.1.0 bitops_1.0-7 magrittr_2.0.1 tibble_3.1.2
[45] crayon_1.4.1 pkgconfig_2.0.3 MASS_7.3-54 ellipsis_0.3.2
[49] Matrix_1.3-3 data.table_1.14.0 assertthat_0.2.1 minqa_1.2.4
[53] rstudioapi_0.13 R6_2.5.0 boot_1.3-28 nlme_3.1-152
[57] compiler_4.1.0
Is there a problem in the matching code?
Mateusz Staniak
Jul 1, 2021, 7:21:05 AM7/1/21
to MSstats
Hi,
can you provide a small sample of quant data and the annotation file? What are the channels in your annotation?
Kind regards
Mateusz
Tobias Kockmann
Jul 1, 2021, 7:56:55 AM7/1/21
to MSstats
> head(raw.pd)
PSMs.Workflow.ID PSMs.Peptide.ID Checked Confidence Identifying.Node PSM.Ambiguity Annotated.Sequence
1 -130 190 False High Sequest HT (A2) Unambiguous [M].sSGAHGEEGSAR.[M]
2 -130 2468088 False High Sequest HT (A2) Unambiguous [R].LQAGEETASHYR.[M]
3 -130 4196087 False High Sequest HT (A2) Unambiguous [R].EmEENFALEAANYQDTIGR.[L]
4 -130 4195766 False High Sequest HT (A2) Unambiguous [R].LLLNNDNLLR.[E]
5 -130 4195756 False High Sequest HT (A2) Unambiguous [R].ILDLGITGPEGH.[V]
6 -130 4195603 False High Sequest HT (A2) Unambiguous [R].FDFPDELR.[P]
Modifications Number.of.Proteins Master.Protein.Accessions Protein.Accessions
1 N-Term(TMT6plex) 2 P43024 P43024; Q9DCW5
2 1 Q9Z0E0 Q9Z0E0
3 M2(Oxidation) 2 P20152 A0A0A6YWC8; P20152
4 6 A0A0N4SVM0 P47753; Q5RKN9; A0A0N4SVM0; P47754; D6RCW7; A0A0G2JE27
5 1 O08553 O08553
6 4 P20917 P20917; A0A087WPP5; Q3ZB60; A0A087WRD6
Number.of.Missed.Cleavages Charge Delta.Score Delta.Cn Rank Search.Engine.Rank mz.in.Da MHplus.in.Da
1 0 3 0.7079 0 1 1 458.5591 1373.663
2 0 3 0.6092 0 1 1 454.5529 1361.644
3 0 2 0.8152 0 1 1 1108.9928 2216.978
4 0 2 0.4677 0 1 1 599.3513 1197.695
5 0 2 0.6702 0 1 1 611.3274 1221.648
6 0 2 0.3274 0 1 1 519.7482 1038.489
Theo.MHplus.in.Da Delta.M.in.ppm Delta.mz.in.Da Activation.Type MS.Order Isolation.Interference.in.Percent
1 1373.661 1.59 0.00073 HCD MS2 1.901614
2 1361.644 -0.30 -0.00013 HCD MS2 19.211230
3 2216.976 0.84 0.00093 HCD MS2 0.000000
4 1197.695 0.20 0.00012 HCD MS2 11.185880
5 1221.647 0.21 0.00013 HCD MS2 18.319190
6 1038.489 0.09 0.00005 HCD MS2 21.923960
Average.Reporter.SN Ion.Inject.Time.in.ms RT.in.min First.Scan Spectrum.File
1 128.4 97.088 13.9462 2136 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw
2 33.0 105.000 26.1383 6737 20200703_027_S219787_TMT-TAILS6plex_set3_pre_2.raw
3 NA 105.000 75.3362 27027 20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw
4 3.3 105.000 75.2028 26968 20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw
5 1.6 105.000 75.1984 26967 20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw
6 6.6 105.000 75.0978 26923 20200703_031_S219788_TMT-TAILS6plex_set4_pre_3.raw
File.ID Abundance.126 Abundance.127 Abundance.128 Abundance.129 Abundance.130 Abundance.131 Quan.Info XCorr
1 F1.4 104.8 129.1 116.0 154.2 109.9 156.4 4.04
2 F2.2 23.9 33.4 22.7 37.0 26.4 54.3 NoQuanLabels 2.84
3 F3.3 NA NA NA NA NA NA NoQuanLabels 4.60
4 F3.3 2.5 NA 3.4 5.9 5.0 2.8 NoQuanLabels 1.86
5 F3.3 2.7 NA NA NA 2.5 4.5 NoQuanLabels 1.88
6 F3.3 6.7 4.0 8.8 9.0 5.0 5.8 NoQuanLabels 1.68
Number.of.Protein.Groups Percolator.q.Value Percolator.PEP
1 1 2.117e-05 1.045e-08
2 1 2.117e-05 5.561e-04
3 1 2.117e-05 5.251e-09
4 1 2.117e-05 3.899e-05
5 1 2.117e-05 6.265e-04
6 1 2.117e-05 1.116e-03
> head(annotation.pd)
Run Fraction TechRepMixture Channel time genotype Mixture
1 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 126 8w ko set1
2 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 127 7d ko set1
3 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 128 8w wt set1
4 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 129 Nv ko set1
5 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 130 7d wt set1
6 20200703_005_S219785_TMT-TAILS6plex_set1_post_1.raw post 1 131 Nv wt set1
BioReplicate Condition
1 TLR4_8w_10 8w_ko
2 TLR4_7d_14 7d_ko
3 WT_8w_14 8w_wt
4 TLR4_Nv_13 Nv_ko
5 WT_7d_4 7d_wt
6 WT_Nv_4 Nv_wt
Mateusz Staniak
Jul 1, 2021, 8:04:11 AM7/1/21
to MSstats
Hi,
csv files or RDS/rda/Rdata files would be much easier to use. Thanks in advance
One protein + annotation should be enough as long as it reproduces the error
One protein + annotation should be enough as long as it reproduces the error
Kind regards
Mateusz
Mateusz Staniak
Jul 1, 2021, 8:42:29 AM7/1/21
to MSstats
Hi,
I got the same error on this test dataset.
The protein you sent me is actually a protein group. The useNumProteinsColumn parameter controls what PD converter does with protein groups. Please try setting this parameter to FALSE or using different column as protein ID. Can't tell if this will fix the problem for full dataset. Please let me know if the error persists.
Kind regards
Mateusz
Tobias Kockmann
Jul 1, 2021, 9:08:38 AM7/1/21
to MSstats
all of these commands give the same error:
input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd)
input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = FALSE)
input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = FALSE, which.proteinid = "Master.Protein.Accessions")
input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, which.proteinid = "Master.Protein.Accessions")
Mateusz Staniak
Jul 1, 2021, 9:10:40 AM7/1/21
to MSstats
Thanks for checking, then please send me a different subset of data that will produce the error with
input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = FALSE)
input.pd
<- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation =
annotation.pd, useNumProteinsColumn = FALSE, which.proteinid =
"Master.Protein.Accessions")
calls
Tobias Kockmann
Jul 1, 2021, 9:10:49 AM7/1/21
to MSstats
How is your code matching the Abundance column in the PSM report with the annotation file?
Mateusz Staniak
Jul 1, 2021, 9:15:08 AM7/1/21
to MSstats
That shouldn't be a problem - it matched correctly for the protein you sent me when the protein group was not removed. Before, the error was caused by the fact that all the data were filtered out, so unique(input$Channel) was empty, and unique(annotation$Channel) was not. This is why I need to see some more data to see the error not confounded with a different problem
To answer your question, columns are converted: Abundance.130 -> Abundance130, melted to a Channel column Abundance130 -> 130 and then merged with the annotation.
Mateusz Staniak
Jul 1, 2021, 9:33:40 AM7/1/21
to MSstats
When I look at your post here, I only see channels 126, 127, 128, 129, 130, 131. But when I load your data, there are columns "Abundance..126" "Abundance..127N"
[36] "Abundance..127C" "Abundance..128N" "Abundance..128C" "Abundance..129N" "Abundance..129C"
[41] "Abundance..130N" "Abundance..130C" "Abundance..131"
are we looking at the same dataset? raw.pd you sent me might be the example dataset from MSstatsTMT package
Tobias Kockmann
Jul 1, 2021, 10:20:37 AM7/1/21
to MSstats
Daaammm, my mistake. I used the same object names as for the example data and cleaned the workspace at some point in the IDE. Stupid me! Now
useNumProteinsColumn = FALSE
does the job as you predicted:
> input.pd <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = FALSE)
INFO [2021-07-01 16:09:49] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-07-01 16:09:53] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-01 16:09:53] ** Using provided annotation.
INFO [2021-07-01 16:09:53] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-01 16:09:53] ** The following options are used:
INFO [2021-07-01 16:09:53] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-01 16:09:53] ** Using provided annotation.
INFO [2021-07-01 16:09:53] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-01 16:09:53] ** The following options are used:
- Features will be defined by the columns: PeptideSequence, PrecursorCharge
- Shared peptides will be removed.
- Proteins with single feature will not be removed.
- Features with less than 3 measurements within each run will be removed.
INFO [2021-07-01 16:09:53] ** Features with all missing measurements across channels within each run are removed.
INFO [2021-07-01 16:09:54] ** Shared peptides are removed.
INFO [2021-07-01 16:09:54] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-01 16:12:15] ** PSMs have been aggregated to peptide ions.
INFO [2021-07-01 16:12:18] ** Run annotation merged with quantification data.
INFO [2021-07-01 16:12:20] ** For peptides overlapped between fractions of set3_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:20] ** For peptides overlapped between fractions of set4_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:21] ** For peptides overlapped between fractions of set2_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:22] ** For peptides overlapped between fractions of set3_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:22] ** For peptides overlapped between fractions of set4_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:23] ** For peptides overlapped between fractions of set3_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:24] ** For peptides overlapped between fractions of set2_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:24] ** For peptides overlapped between fractions of set4_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:25] ** For peptides overlapped between fractions of set1_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:26] ** For peptides overlapped between fractions of set1_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:27] ** For peptides overlapped between fractions of set2_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:28] ** For peptides overlapped between fractions of set1_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:28] ** Fractions belonging to same mixture have been combined.
INFO [2021-07-01 16:12:28] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-01 16:12:28] ** Fractionation handled.
INFO [2021-07-01 16:12:29] ** Updated quantification data to make balanced design. Missing values are marked by NA
INFO [2021-07-01 16:12:29] ** Finished preprocessing. The dataset is ready to be processed by the proteinSummarization function.
INFO [2021-07-01 16:09:54] ** Shared peptides are removed.
INFO [2021-07-01 16:09:54] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-01 16:12:15] ** PSMs have been aggregated to peptide ions.
INFO [2021-07-01 16:12:18] ** Run annotation merged with quantification data.
INFO [2021-07-01 16:12:20] ** For peptides overlapped between fractions of set3_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:20] ** For peptides overlapped between fractions of set4_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:21] ** For peptides overlapped between fractions of set2_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:22] ** For peptides overlapped between fractions of set3_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:22] ** For peptides overlapped between fractions of set4_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:23] ** For peptides overlapped between fractions of set3_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:24] ** For peptides overlapped between fractions of set2_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:24] ** For peptides overlapped between fractions of set4_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:25] ** For peptides overlapped between fractions of set1_1 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:26] ** For peptides overlapped between fractions of set1_2 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:27] ** For peptides overlapped between fractions of set2_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:28] ** For peptides overlapped between fractions of set1_3 use the fraction with maximal average abundance.
INFO [2021-07-01 16:12:28] ** Fractions belonging to same mixture have been combined.
INFO [2021-07-01 16:12:28] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-01 16:12:28] ** Fractionation handled.
INFO [2021-07-01 16:12:29] ** Updated quantification data to make balanced design. Missing values are marked by NA
INFO [2021-07-01 16:12:29] ** Finished preprocessing. The dataset is ready to be processed by the proteinSummarization function.
Mateusz Staniak
Jul 1, 2021, 6:21:03 PM7/1/21
to MSstats
Hi,
glad to hear it works! Now it should work with both useNumProteinsColumn = FALSE and useNumProteinsColumn = TRUE
Best,
Mateusz
Tobias Kockmann
Jul 2, 2021, 3:08:22 AM7/2/21
to MSstats
unfortunately not:
> input.pd.master <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = FALSE, which.proteinid = "Master.Protein.Accessions")
INFO [2021-07-02 08:58:27] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-07-02 08:58:31] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-02 08:58:31] ** Using provided annotation.
INFO [2021-07-02 08:58:31] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-02 08:58:31] ** The following options are used:
INFO [2021-07-02 08:58:27] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-07-02 08:58:31] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-02 08:58:31] ** Using provided annotation.
INFO [2021-07-02 08:58:31] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-02 08:58:31] ** The following options are used:
- Features will be defined by the columns: PeptideSequence, PrecursorCharge
- Shared peptides will be removed.
- Proteins with single feature will not be removed.
- Features with less than 3 measurements within each run will be removed.
INFO [2021-07-02 08:58:32] ** Features with all missing measurements across channels within each run are removed.
INFO [2021-07-02 08:58:33] ** Shared peptides are removed.
INFO [2021-07-02 08:58:33] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:00:56] ** PSMs have been aggregated to peptide ions.
INFO [2021-07-02 09:00:59] ** Run annotation merged with quantification data.
INFO [2021-07-02 09:01:01] ** For peptides overlapped between fractions of set3_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:01] ** For peptides overlapped between fractions of set4_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:02] ** For peptides overlapped between fractions of set2_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:03] ** For peptides overlapped between fractions of set3_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:03] ** For peptides overlapped between fractions of set4_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:04] ** For peptides overlapped between fractions of set3_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:04] ** For peptides overlapped between fractions of set2_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:05] ** For peptides overlapped between fractions of set4_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:06] ** For peptides overlapped between fractions of set1_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:06] ** For peptides overlapped between fractions of set1_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:07] ** For peptides overlapped between fractions of set2_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:07] ** For peptides overlapped between fractions of set1_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:08] ** Fractions belonging to same mixture have been combined.
INFO [2021-07-02 09:01:08] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:01:08] ** Fractionation handled.
INFO [2021-07-02 09:01:09] ** Updated quantification data to make balanced design. Missing values are marked by NA
INFO [2021-07-02 09:01:10] ** Finished preprocessing. The dataset is ready to be processed by the proteinSummarization function.
> ?PDtoMSstatsTMTFormat
> input.pd.master.noSharedPeptides <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = TRUE, which.proteinid = "Master.Protein.Accessions")
INFO [2021-07-02 09:05:16] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-07-02 09:05:20] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-02 09:05:20] ** Using provided annotation.
INFO [2021-07-02 09:05:20] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-02 09:05:20] ** The following options are used:
INFO [2021-07-02 08:58:33] ** Shared peptides are removed.
INFO [2021-07-02 08:58:33] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:00:56] ** PSMs have been aggregated to peptide ions.
INFO [2021-07-02 09:00:59] ** Run annotation merged with quantification data.
INFO [2021-07-02 09:01:01] ** For peptides overlapped between fractions of set3_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:01] ** For peptides overlapped between fractions of set4_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:02] ** For peptides overlapped between fractions of set2_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:03] ** For peptides overlapped between fractions of set3_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:03] ** For peptides overlapped between fractions of set4_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:04] ** For peptides overlapped between fractions of set3_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:04] ** For peptides overlapped between fractions of set2_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:05] ** For peptides overlapped between fractions of set4_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:06] ** For peptides overlapped between fractions of set1_1 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:06] ** For peptides overlapped between fractions of set1_2 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:07] ** For peptides overlapped between fractions of set2_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:07] ** For peptides overlapped between fractions of set1_3 use the fraction with maximal average abundance.
INFO [2021-07-02 09:01:08] ** Fractions belonging to same mixture have been combined.
INFO [2021-07-02 09:01:08] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:01:08] ** Fractionation handled.
INFO [2021-07-02 09:01:09] ** Updated quantification data to make balanced design. Missing values are marked by NA
INFO [2021-07-02 09:01:10] ** Finished preprocessing. The dataset is ready to be processed by the proteinSummarization function.
> ?PDtoMSstatsTMTFormat
> input.pd.master.noSharedPeptides <- MSstatsTMT::PDtoMSstatsTMTFormat(input = raw.pd, annotation = annotation.pd, useNumProteinsColumn = TRUE, which.proteinid = "Master.Protein.Accessions")
INFO [2021-07-02 09:05:16] ** Raw data from ProteomeDiscoverer imported successfully.
INFO [2021-07-02 09:05:20] ** Raw data from ProteomeDiscoverer cleaned successfully.
INFO [2021-07-02 09:05:20] ** Using provided annotation.
INFO [2021-07-02 09:05:20] ** Run and Channel labels were standardized to remove symbols such as '.' or '%'.
INFO [2021-07-02 09:05:20] ** The following options are used:
- Features will be defined by the columns: PeptideSequence, PrecursorCharge
- Shared peptides will be removed.
- Proteins with single feature will not be removed.
- Features with less than 3 measurements within each run will be removed.
INFO [2021-07-02 09:05:20] ** Features with all missing measurements across channels within each run are removed.
INFO [2021-07-02 09:05:20] ** Shared peptides are removed.
INFO [2021-07-02 09:05:20] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:05:20] ** PSMs have been aggregated to peptide ions.
INFO [2021-07-02 09:05:20] ** Shared peptides are removed.
INFO [2021-07-02 09:05:20] ** Features with one or two measurements across channels within each run are removed.
INFO [2021-07-02 09:05:20] ** PSMs have been aggregated to peptide ions.
Error in .mergeAnnotation(input, annotation) :
** Please check the annotation file. The channel name must be matched with that in input data.
Mateusz Staniak
Jul 2, 2021, 5:18:23 AM7/2/21
to MSstats
Hi,
thanks for letting me know,
it looks like in this case every protein is either a group or filtered out based on other criteria, that's interesting,
we will need to describe the useNumProteinsColumn parameter in the documentation better
Best,
Mateusz
Mateusz
Tobias Kockmann
Jul 2, 2021, 5:36:06 AM7/2/21
to MSstats
Since you mention the documentation. I am not sure what to make of:
useNumProteinsColumn
logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet.
useUniquePeptide
logical, if TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.
logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet.
useUniquePeptide
logical, if TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.
It kind of sounds like both parameters are doing the same thing. Setting useNumProteinsColumn = TRUE will remove all peptides with Number.of.Proteins > 1 ??? How is uniqueness judged? Where is the difference between being unique and being assigned to a signle protein/protein group???
Mateusz Staniak
Jul 2, 2021, 6:04:09 AM7/2/21
to MSstats
Hi,
this is PD-specific. In most converters, we remove shared peptides simply by counting proteins per peptide (unique = count == 1) - that' what the useUniquePeptide parameter does. In PD, there is additional information in the column with protein counts. This way, user can remove peptides that belong to more than one protein according to PD counts (in this case, these proteins are in a single protein group). This second meaning is not used in any other converter.
Best,
Mateusz
Mateusz
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