LC-MS file annotation -> MSstats #183
Description
Dear FragPipe developers,
I would like to make you aware of the following:
Your FragPipe tutorial suggests to use Replicate labels that are only unique within levels of Experiment, but not across! This information is also passed on to the MSstats.csv. This will lead to potentially unexpected results when running MSstats on this output. In a nutshell, it will instruct MSstats to generate linear mixed effect (LME) models that assume repeated sampling (nested experimental design). Here is an example for n = 7 and two experimental groups:
will fit: lmer(formula = ABUNDANCE ~ GROUP + (1|SUBJECT), data = …)
vs.
will fit: lm(formula = ABUNDANCE ~ GROUP, data = …)
which has a strong impact on the test results (p-value distribution):
VolcanoPlot-6.pdf
VolcanoPlot-7.pdf
Maybe it would be good to align the two software packages?
Best,
Tobi
> sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.4
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readr_1.3.1 MSstats_3.18.5
loaded via a namespace (and not attached):
[1] gtools_3.8.1 statmod_1.4.34 minpack.lm_1.2-1
[4] tidyselect_1.0.0 reshape2_1.4.3 purrr_0.3.3
[7] splines_3.6.3 lattice_0.20-40 colorspace_1.4-1
[10] vctrs_0.2.4 generics_0.0.2 doSNOW_1.0.18
[13] snow_0.4-3 yaml_2.2.1 marray_1.64.0
[16] survival_3.1-11 rlang_0.4.5 nloptr_1.2.2.1
[19] pillar_1.4.3 glue_1.3.2 plyr_1.8.6
[22] foreach_1.4.8 lifecycle_0.2.0 stringr_1.4.0
[25] munsell_0.5.0 gtable_0.3.0 caTools_1.18.0
[28] codetools_0.2-16 labeling_0.3 parallel_3.6.3
[31] preprocessCore_1.48.0 broom_0.5.5 Rcpp_1.0.4
[34] KernSmooth_2.23-16 scales_1.1.0 backports_1.1.5
[37] limma_3.42.2 gdata_2.18.0 farver_2.0.3
[40] lme4_1.1-21 gplots_3.0.3 digest_0.6.25
[43] hms_0.5.3 ggplot2_3.3.0 stringi_1.4.6
[46] dplyr_0.8.5 ggrepel_0.8.2 grid_3.6.3
[49] tools_3.6.3 bitops_1.0-6 magrittr_1.5
[52] tibble_2.1.3 crayon_1.3.4 tidyr_1.0.2
[55] pkgconfig_2.0.3 MASS_7.3-51.5 Matrix_1.2-18
[58] data.table_1.12.8 assertthat_0.2.1 minqa_1.2.4
[61] rstudioapi_0.11 iterators_1.0.12 R6_2.4.1
[64] boot_1.3-24 nlme_3.1-145 compiler_3.6.3
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