FragPipeAnalystR LFQ tutorial
Introduction
Here we presented the usage of FragPipeAnalystR to reproduce AP-MS analysis previously demonstrated in the manuscript. Note that in the manuscript, we used the FragPipeAnalyst website, but you could reproduce the same analysis with FragPipeR. You can download the example files from here. Files are in “AP-MS” folder.
Reading input files
library(FragPipeAnalystR)## se <- make_se_from_files("/Users/hsiaoyi/Documents/workspace/FragPipeR_manuscript/data/AP-MS/combined_protein.tsv",
"/Users/hsiaoyi/Documents/workspace/FragPipeR_manuscript/data/AP-MS/experiment_annotation.tsv",
type = "LFQ", level = "protein")print(head(rownames(se)))## [1] "A0A075B6R9" "A0A075B6S2" "A0A0C4DH68" "A0A2R8Y4L2" "A0FGR8"
## [6] "A0MZ66"plot_pca(se)
plot_correlation_heatmap(se)
plot_missval_heatmap(se)
plot_feature_numbers(se)
colData(se)$condition## [1] "CCND1" "CCND1" "CCND1" "CONTROL" "CONTROL" "CONTROL" "CONTROL"Imputation
imputed_se <- manual_impute(se)plot_pca(imputed_se)
plot_correlation_heatmap(imputed_se)
Differential expression analysis
de_result <- test_limma(imputed_se, type = "all")## Tested contrasts: CCND1_vs_CONTROLde_result_updated <- add_rejections(de_result)plot_volcano(de_result_updated, "CCND1_vs_CONTROL")
The volcano could be labelled in a different way via
name_col argument of the function:
plot_volcano(de_result_updated, "CCND1_vs_CONTROL", name_col="Gene")
sessionInfo()## R version 4.4.1 (2024-06-14)
## Platform: aarch64-apple-darwin20
## Running under: macOS Ventura 13.4
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: America/Detroit
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices datasets utils methods base
##
## other attached packages:
## [1] FragPipeAnalystR_1.0.5
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## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3 rstudioapi_0.17.1
## [3] jsonlite_1.8.9 shape_1.4.6.1
## [5] MultiAssayExperiment_1.32.0 magrittr_2.0.3
## [7] ggtangle_0.0.6 farver_2.1.2
## [9] MALDIquant_1.22.3 rmarkdown_2.29
## [11] GlobalOptions_0.1.2 fs_1.6.5
## [13] zlibbioc_1.52.0 vctrs_0.6.5
## [15] memoise_2.0.1 ggtree_3.14.0
## [17] htmltools_0.5.8.1 S4Arrays_1.6.0
## [19] gridGraphics_0.5-1 SparseArray_1.6.1
## [21] mzID_1.44.0 sass_0.4.9
## [23] bslib_0.9.0 htmlwidgets_1.6.4
## [25] plyr_1.8.9 plotly_4.10.4
## [27] impute_1.80.0 cachem_1.1.0
## [29] igraph_2.1.4 lifecycle_1.0.4
## [31] iterators_1.0.14 pkgconfig_2.0.3
## [33] gson_0.1.0 Matrix_1.7-0
## [35] R6_2.5.1 fastmap_1.2.0
## [37] GenomeInfoDbData_1.2.13 MatrixGenerics_1.18.1
## [39] clue_0.3-66 fdrtool_1.2.18
## [41] aplot_0.2.4 digest_0.6.37
## [43] enrichplot_1.26.6 pcaMethods_1.98.0
## [45] colorspace_2.1-1 patchwork_1.3.0
## [47] AnnotationDbi_1.68.0 S4Vectors_0.44.0
## [49] GenomicRanges_1.58.0 RSQLite_2.3.9
## [51] labeling_0.4.3 cytolib_2.18.2
## [53] httr_1.4.7 abind_1.4-8
## [55] compiler_4.4.1 withr_3.0.2
## [57] bit64_4.6.0-1 doParallel_1.0.17
## [59] ConsensusClusterPlus_1.70.0 BiocParallel_1.40.0
## [61] DBI_1.2.3 ExPosition_2.8.23
## [63] R.utils_2.12.3 MASS_7.3-60.2
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## [67] rjson_0.2.23 mzR_2.40.0
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## [73] glue_1.8.0 nlme_3.1-164
## [75] QFeatures_1.16.0 GOSemSim_2.32.0
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## [79] cluster_2.1.6 reshape2_1.4.4
## [81] fgsea_1.32.2 generics_0.1.3
## [83] gtable_0.3.6 tzdb_0.4.0
## [85] R.methodsS3_1.8.2 preprocessCore_1.68.0
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## [91] BiocGenerics_0.52.0 ggrepel_0.9.6
## [93] foreach_1.5.2 pillar_1.10.1
## [95] stringr_1.5.1 yulab.utils_0.2.0
## [97] limma_3.62.2 flowCore_2.18.0
## [99] circlize_0.4.16 splines_4.4.1
## [101] dplyr_1.1.4 treeio_1.30.0
## [103] lattice_0.22-6 renv_1.1.0
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## [109] ComplexHeatmap_2.22.0 Biostrings_2.74.1
## [111] alluvial_0.1-2 knitr_1.49
## [113] IRanges_2.40.1 ProtGenerics_1.38.0
## [115] SummarizedExperiment_1.36.0 stats4_4.4.1
## [117] xfun_0.50 Biobase_2.66.0
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## [121] matrixStats_1.5.0 stringi_1.8.4
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## [131] qvalue_2.38.0 BiocManager_1.30.25
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## [135] affyio_1.76.0 munsell_0.5.1
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## [143] assertthat_0.2.1 readr_2.1.5
## [145] ggplot2_3.5.1 blob_1.2.4
## [147] clusterProfiler_4.14.4 DOSE_4.0.0
## [149] AnnotationFilter_1.30.0 viridisLite_0.4.2
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## [153] affy_1.84.0 ncdf4_1.23
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## [161] vsn_3.74.0 KEGGREST_1.46.0
## [163] SNFtool_2.3.1