数据准备
我们将使用 前一步 中的数据集。
library(tidymass)
#> Registered S3 method overwritten by 'Hmisc':
#> method from
#> vcov.default fit.models
#> ── Attaching packages ──────────────────────────────────────── tidymass 1.0.9 ──
#> ✔ massdataset 1.0.34 ✔ metid 1.2.34
#> ✔ massprocesser 1.0.10 ✔ masstools 1.0.13
#> ✔ masscleaner 1.0.12 ✔ dplyr 1.1.4
#> ✔ massqc 1.0.7 ✔ ggplot2 3.5.1
#> ✔ massstat 1.0.6 ✔ magrittr 2.0.3
#> ✔ metpath 1.0.8
load("data_cleaning/POS/object_pos2")
load("data_cleaning/NEG/object_neg2")
将 MS2 光谱数据添加到 mass_dataset 类
下载 MS2 数据。
解压数据。
正模式
object_pos2 <-
mutate_ms2(
object = object_pos2,
column = "rp",
polarity = "positive",
ms1.ms2.match.mz.tol = 15,
ms1.ms2.match.rt.tol = 30,
path = "mgf_ms2_data/POS"
)
#> Reading mgf data...
#> Reading mgf data...
#> Reading mgf data...
#> Reading mgf data...
#> 1042 out of 5101 variable have MS2 spectra.
#> Selecting the most intense MS2 spectrum for each peak...
object_pos2
#> --------------------
#> massdataset version: 0.99.8
#> --------------------
#> 1.expression_data:[ 5101 x 259 data.frame]
#> 2.sample_info:[ 259 x 6 data.frame]
#> 259 samples:sample_06 sample_103 sample_11 ... sample_QC_38 sample_QC_39
#> 3.variable_info:[ 5101 x 6 data.frame]
#> 5101 variables:M70T53_POS M70T527_POS M71T775_POS ... M836T610_POS M836T759_POS
#> 4.sample_info_note:[ 6 x 2 data.frame]
#> 5.variable_info_note:[ 6 x 2 data.frame]
#> 6.ms2_data:[ 1042 variables x 951 MS2 spectra]
#> --------------------
#> Processing information
#> 9 processings in total
#> Latest 3 processings show
#> normalize_data ----------
#> Package Function.used Time
#> 1 masscleaner normalize_data() 2024-09-25 21:03:38
#> integrate_data ----------
#> Package Function.used Time
#> 1 masscleaner integrate_data() 2024-09-25 21:03:38
#> mutate_ms2 ----------
#> Package Function.used Time
#> 1 massdataset mutate_ms2() 2024-09-25 21:37:01
extract_ms2_data(object_pos2)
#> $`QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf`
#> --------------------
#> column: rp
#> polarity: positive
#> mz_tol: 15
#> rt_tol (second): 30
#> --------------------
#> 1042 variables:
#> M71T775_POS M72T53_POS M83T50_POS M84T57_POS M85T54_POS...
#> 951 MS2 spectra.
#> mz70.981170654297rt775.4286 mz72.081642150879rt53.6528862 mz82.945625305176rt49.238013 mz84.045127868652rt59.6895132 mz85.029016959043rt53.0835648...
负模式
object_neg2 <-
mutate_ms2(
object = object_neg2,
column = "rp",
polarity = "negative",
ms1.ms2.match.mz.tol = 15,
ms1.ms2.match.rt.tol = 30,
path = "mgf_ms2_data/NEG"
)
#> Reading mgf data...
#> Reading mgf data...
#> Reading mgf data...
#> Reading mgf data...
#> 1092 out of 4104 variable have MS2 spectra.
#> Selecting the most intense MS2 spectrum for each peak...
object_neg2
#> --------------------
#> massdataset version: 0.99.8
#> --------------------
#> 1.expression_data:[ 4104 x 259 data.frame]
#> 2.sample_info:[ 259 x 6 data.frame]
#> 259 samples:sample_06 sample_103 sample_11 ... sample_QC_38 sample_QC_39
#> 3.variable_info:[ 4104 x 6 data.frame]
#> 4104 variables:M70T712_NEG M70T587_NEG M71T587_NEG ... M884T57_NEG M899T56_NEG
#> 4.sample_info_note:[ 6 x 2 data.frame]
#> 5.variable_info_note:[ 6 x 2 data.frame]
#> 6.ms2_data:[ 1092 variables x 988 MS2 spectra]
#> --------------------
#> Processing information
#> 9 processings in total
#> Latest 3 processings show
#> normalize_data ----------
#> Package Function.used Time
#> 1 masscleaner normalize_data() 2024-09-25 21:03:40
#> integrate_data ----------
#> Package Function.used Time
#> 1 masscleaner integrate_data() 2024-09-25 21:03:40
#> mutate_ms2 ----------
#> Package Function.used Time
#> 1 massdataset mutate_ms2() 2024-09-25 21:37:13
extract_ms2_data(object_neg2)
#> $`QEP_SGA_QC_neg_ms2_ce25_01.mgf;QEP_SGA_QC_neg_ms2_ce25_02.mgf;QEP_SGA_QC_neg_ms2_ce50_01.mgf;QEP_SGA_QC_neg_ms2_ce50_02.mgf`
#> --------------------
#> column: rp
#> polarity: negative
#> mz_tol: 15
#> rt_tol (second): 30
#> --------------------
#> 1092 variables:
#> M71T51_NEG M73T74_NEG M75T52_NEG M80T299_NEG M80T232_NEG...
#> 988 MS2 spectra.
#> mz71.012359619141rt52.3270968 mz73.02799987793rt74.779476 mz75.007308959961rt24.1557228 mz79.955728954783rt301.268466 mz79.955834350356rt235.127328...
代谢物注释
代谢物注释基于 metID 包。
下载数据库
我们需要从 metID 网站 下载 MS2 数据库。
这里我们下载 Michael Snyder RPLC 数据库、Orbitrap 数据库 和 MoNA 数据库，并将它们放入名为 metabolite_annotation 的新文件夹中。
正模式
使用 snyder_database_rplc0.0.3 注释特征。
load("metabolite_annotation/snyder_database_rplc0.0.3.rda")
snyder_database_rplc0.0.3
#> -----------Base information------------
#> Version:0.0.2
#> Source:MS
#> Link:http://snyderlab.stanford.edu/
#> Creater:Xiaotao Shen(shenxt1990@163.com)
#> With RT information
#> -----------Spectral information------------
#> 14 items of metabolite information:
#> Lab.ID; Compound.name; mz; RT; CAS.ID; HMDB.ID; KEGG.ID; Formula; mz.pos; mz.neg (top10)
#> 917 metabolites in total.
#> 356 metabolites with spectra in positive mode.
#> 534 metabolites with spectra in negative mode.
#> Collision energy in positive mode (number:):
#> Total number:2
#> NCE25; NCE50
#> Collision energy in negative mode:
#> Total number:2
#> NCE25; NCE50
object_pos2 <-
annotate_metabolites(
object = object_pos2,
database = snyder_database_rplc0.0.3,
based_on = c("ms1", "rt", "ms2"),
polarity = "positive",
column = "rp",
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
使用 orbitrap_database0.0.3 注释特征。
load("metabolite_annotation/orbitrap_database0.0.3.rda")
orbitrap_database0.0.3
#> -----------Base information------------
#> Version:0.0.1
#> Source:NIST
#> Link:https://www.nist.gov/
#> Creater:Xiaotao Shen(shenxt1990@163.com)
#> Without RT informtaion
#> -----------Spectral information------------
#> 8 items of metabolite information:
#> Lab.ID; Compound.name; mz; RT; CAS.ID; HMDB.ID; KEGG.ID; Formula
#> 8360 metabolites in total.
#> 7103 metabolites with spectra in positive mode.
#> 3311 metabolites with spectra in negative mode.
#> Collision energy in positive mode (number:):
#> Total number:12
#> 10; 15; 45; 55; 5; 20; 30; 35; 40; 25
#> Collision energy in negative mode:
#> Total number:12
#> 10; 25; 5; 15; 20; 30; 50; 35; 40; 45
object_pos2 <-
annotate_metabolites(
object = object_pos2,
ms1.match.ppm = 15,
polarity = "positive",
column = "rp",
database = orbitrap_database0.0.3,
based_on = c("ms1", "ms2"),
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
使用 mona_database0.0.3 注释特征。
load("metabolite_annotation/mona_database0.0.3.rda")
mona_database0.0.3
#> -----------Base information------------
#> Version:0.0.1
#> Source:MoNA
#> Link:http://mona.fiehnlab.ucdavis.edu/
#> Creater:Xiaotao Shen(shenxt1990@163.com)
#> Without RT informtaion
#> -----------Spectral information------------
#> 25 items of metabolite information:
#> Lab.ID; Compound.name; mz; RT; CAS.ID; HMDB.ID; KEGG.ID; Formula; CE; Chebi.ID (top10)
#> 19537 metabolites in total.
#> 9307 metabolites with spectra in positive mode.
#> 10243 metabolites with spectra in negative mode.
#> Collision energy in positive mode (number:):
#> Total number:284
#> Ramp 21.1-31.6; Ramp 20.8-31.3; 20; 30; 40; 50; 10; Ramp 21.8-32.7; Ramp 18.5-27.8; Ramp 20.5-30.7
#> Collision energy in negative mode:
#> Total number:217
#> 10; 20; 30; 40; 50; 35 % (nominal); 15 % (nominal); 30 % (nominal); 45 % (nominal); 60 % (nominal)
object_pos2 <-
annotate_metabolites(
object = object_pos2,
ms1.match.ppm = 15,
polarity = "positive",
column = "rp",
database = mona_database0.0.3,
based_on = c("ms1", "ms2"),
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
负模式
使用 snyder_database_rplc0.0.3 注释特征。
object_neg2 <-
annotate_metabolites(
object = object_neg2,
ms1.match.ppm = 15,
rt.match.tol = 30,
polarity = "negative",
column = "rp",
database = snyder_database_rplc0.0.3,
based_on = c("ms1", "rt", "ms2"),
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
使用 orbitrap_database0.0.3 注释特征。
object_neg2 <-
annotate_metabolites(
object = object_neg2,
ms1.match.ppm = 15,
polarity = "negative",
column = "rp",
database = orbitrap_database0.0.3,
based_on = c("ms1", "ms2"),
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
使用 mona_database0.0.3 注释特征。
object_neg2 <-
annotate_metabolites(
object = object_neg2,
ms1.match.ppm = 15,
polarity = "negative",
column = "rp",
database = mona_database0.0.3,
based_on = c("ms1", "ms2"),
adduct.table = NULL
)
#> No adduct table is provided. Use the default adduct table.
#> Checking parameters...
#> All parameters are correct.
#>
#> Use all CE values.
#>
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#> All done.
注释结果
注释结果将作为 mass_dataset 类中的 annotation_table 插槽分配。
head(extract_annotation_table(object = object_pos2))
#> variable_id
#> 1 M100T160_POS
#> 2 M104T51_POS
#> 3 M113T187_POS
#> 4 M113T81_POS
#> 5 M113T81_POS
#> 6 M113T81_POS
#> ms2_files_id
#> 1 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> 2 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> 3 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> 4 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> 5 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> 6 QEP_SGA_QC_posi_ms2_ce25_01.mgf;QEP_SGA_QC_posi_ms2_ce25_02.mgf;QEP_SGA_QC_posi_ms2_ce50_01.mgf;QEP_SGA_QC_posi_ms2_ce50_02.mgf
#> ms2_spectrum_id Compound.name CAS.ID HMDB.ID
#> 1 mz100.076248168945rt158.377638 N-Methyl-2-pyrrolidone 872-50-4 <NA>
#> 2 mz104.107467651367rt49.510314 5-Amino-1-pentanol 2508-29-4 <NA>
#> 3 mz113.060150146484rt188.406384 1,4-Cyclohexanedione <NA> <NA>
#> 4 mz113.035087585449rt77.20827 Uracil 66-22-8 HMDB00300
#> 5 mz113.035087585449rt77.20827 Maleic hydrazide 123-33-1 <NA>
#> 6 mz113.035087585449rt77.20827 Uracil 66-22-8 <NA>
#> KEGG.ID Lab.ID Adduct mz.error mz.match.score RT.error RT.match.score
#> 1 C11118 MONA_11509 (M+H)+ 1.335652 0.9960435 NA NA
#> 2 <NA> NO07238 (M+H)+ 1.169128 0.9969671 NA NA
#> 3 <NA> MONA_14519 (M+H)+ 1.051626 0.9975454 NA NA
#> 4 C00106 NO07292 (M+H)+ 1.218964 0.9967035 NA NA
#> 5 <NA> NO07300 (M+H)+ 1.218964 0.9967035 NA NA
#> 6 C00106 MONA_2762 (M+H)+ 1.275544 0.9963909 NA NA
#> CE SS Total.score Database Level
#> 1 35 (nominal) 0.6871252 0.7442896 MoNA_0.0.1 2
#> 2 5 0.5971697 0.6906242 NIST_0.0.1 2
#> 3 HCD (NCE 20-30-40%) 0.5401414 0.6566000 MoNA_0.0.1 2
#> 4 10 0.6484578 0.7213092 NIST_0.0.1 2
#> 5 20 0.5486434 0.6614205 NIST_0.0.1 2
#> 6 Ramp 5-60 0.5404285 0.6563874 MoNA_0.0.1 2
variable_info_pos <-
extract_variable_info(object = object_pos2)
head(variable_info_pos)
#> variable_id mz rt na_freq na_freq.1 na_freq.2 Compound.name
#> 1 M70T53_POS 70.06596 52.78542 0.00000000 0.14545455 0.00000000 <NA>
#> 2 M70T527_POS 70.36113 526.76657 0.02564103 0.18181818 0.30000000 <NA>
#> 3 M71T775_POS 70.98125 775.44867 0.00000000 0.00000000 0.00000000 <NA>
#> 4 M71T669_POS 70.98125 668.52844 0.00000000 0.02727273 0.01818182 <NA>
#> 5 M71T715_POS 70.98125 714.74066 0.05128205 0.12727273 0.02727273 <NA>
#> 6 M71T54_POS 71.04999 54.45641 0.15384615 0.99090909 0.05454545 <NA>
#> CAS.ID HMDB.ID KEGG.ID Lab.ID Adduct mz.error mz.match.score RT.error
#> 1 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 2 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 3 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 4 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 5 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 6 <NA> <NA> <NA> <NA> <NA> NA NA NA
#> RT.match.score CE SS Total.score Database Level
#> 1 NA <NA> NA NA <NA> NA
#> 2 NA <NA> NA NA <NA> NA
#> 3 NA <NA> NA NA <NA> NA
#> 4 NA <NA> NA NA <NA> NA
#> 5 NA <NA> NA NA <NA> NA
#> 6 NA <NA> NA NA <NA> NA
table(variable_info_pos$Level)
#>
#> 1 2
#> 23 114
table(variable_info_pos$Database)
#>
#> MoNA_0.0.1 MS_0.0.2 NIST_0.0.1
#> 43 23 71
使用 ms2_plot_mass_dataset() 函数获取 MS2 匹配图。
ms2_plot_mass_dataset(object = object_pos2,
variable_id = "M86T95_POS",
database = mona_database0.0.3)
#> $M86T95_POS_1
ms2_plot_mass_dataset(object = object_pos2,
variable_id = "M86T95_POS",
database = mona_database0.0.3,
interactive_plot = TRUE)
#> $M86T95_POS_1
ms2_plot_mass_dataset(object = object_pos2,
variable_id = "M147T54_POS",
database = snyder_database_rplc0.0.3,
interactive_plot = FALSE)
#> database may be wrong.
#> database may be wrong.
#> $M147T54_POS_1
#>
#> $M147T54_POS_2
#>
#> $M147T54_POS_3
保存数据以供后续分析。
save(object_pos2, file = "metabolite_annotation/object_pos2")
save(object_neg2, file = "metabolite_annotation/object_neg2")
会话信息
sessionInfo()
#> R version 4.4.1 (2024-06-14)
#> Platform: aarch64-apple-darwin20
#> Running under: macOS 15.0
#>
#> 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: Asia/Singapore
#> tzcode source: internal
#>
#> attached base packages:
#> [1] grid stats4 stats graphics grDevices utils datasets
#> [8] methods base
#>
#> other attached packages:
#> [1] metid_1.2.34 metpath_1.0.8 ComplexHeatmap_2.20.0
#> [4] mixOmics_6.28.0 lattice_0.22-6 MASS_7.3-61
#> [7] massstat_1.0.6 tidyr_1.3.1 ggfortify_0.4.17
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