vignettes/identify_single_peak.Rmd
identify_single_peak.RmdSome times we only want to match one peak. We can use
identify_single_peak() function to identify single
peak.
We need the m/z, rt and MS2 information. MS2 must be a matrix with
two columns: mz and intensity.
mz <- 472.3032
rt <- 772.906
ms2 <- data.frame(
mz = c(81.38455,82.19755,85.02840,86.5934,86.98958,89.48135,90.70250,
93.03886, 102.09140, 103.03903, 116.01658, 127.98412,
134.06819, 152.46967, 162.02180, 162.05521, 162.11261),
intensity = c(1396.341,1488.730,15473.604, 1740.842,2158.014,1351.686,
1547.099,1325.864,22441.047,76217.016,17809.395,
1439.743, 1729.786, 1543.765, 2228.743,
3508.225, 529120.000),
stringsAsFactors = FALSE
)
ms2 %>% head()
#> mz intensity
#> 1 81.38455 1396.341
#> 2 82.19755 1488.730
#> 3 85.02840 15473.604
#> 4 86.59340 1740.842
#> 5 86.98958 2158.014
#> 6 89.48135 1351.686identify_single_peak()
function
First we load the database from metid package and then
put them in a example folder.
##create a folder named as example
path <- file.path(".", "example")
dir.create(path = path, showWarnings = FALSE)
##get database from metid
data("snyder_database_rplc0.0.3", package = "metid")
save(snyder_database_rplc0.0.3, file = file.path(path, "snyder_database_rplc0.0.3"))Now in your ./example, there are one file, namely
snyder_database_rplc0.0.3.
annotation_result <-
identify_single_peak(ms1.mz = mz,
ms1.rt = rt,
ms2 = ms2,
ms1.match.ppm = 15,
rt.match.tol = 30,
ms2.match.tol = 0.5,
database = "snyder_database_rplc0.0.3",
path = path)
#>
|
| | 0%
|
|======================================================================| 100%annotation_result is a metIdentifyClass
object, so you can use all the functions for it to process.
sessionInfo()
#> R version 4.2.1 (2022-06-23)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur ... 10.16
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#> BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
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#> locale:
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#> attached base packages:
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#> other attached packages:
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#> [9] tidyverse_1.3.1 ggplot2_3.3.6 massdataset_1.0.5 magrittr_2.0.3
#> [13] masstools_0.99.13 metid_1.2.16
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