Package: notame 1.3.0

Vilhelm Suksi

notame: Workflow for non-targeted LC-MS metabolic profiling

Provides functionality for untargeted LC-MS metabolomics research as specified in the associated protocol article in the 'Metabolomics Data Processing and Data Analysis—Current Best Practices' special issue of the Metabolites journal (2020). This includes tabular data preprocessing and quality control, uni- and multivariate analysis as well as quality control visualizations, feature-wise visualizations and results visualizations. Raw data preprocessing and functionality related to biological context, such as pathway analysis, is not included.

Authors:Anton Klåvus [aut, cph], Jussi Paananen [aut, cph], Oskari Timonen [aut, cph], Atte Lihtamo [aut], Vilhelm Suksi [aut, cre], Retu Haikonen [aut], Leo Lahti [aut], Kati Hanhineva [aut], Ville Koistinen [ctb], Olli Kärkkäinen [ctb], Artur Sannikov [ctb]

notame_1.3.0.tar.gz
notame_1.3.0.zip(r-4.7)notame_1.3.0.zip(r-4.6)notame_1.3.0.zip(r-4.5)
notame_1.3.0.tgz(r-4.6-any)notame_1.3.0.tgz(r-4.5-any)
notame_1.3.0.tar.gz(r-4.7-any)notame_1.3.0.tar.gz(r-4.6-any)
notame_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
notame/json (API)
NEWS

# Install 'notame' in R:
install.packages('notame', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hanhineva-lab/notame/issues

Pkgdown/docs site:https://hanhineva-lab.github.io

Datasets:

On BioConductor:notame-1.3.0(bioc 3.24)notame-1.2.0(bioc 3.23)

biomedicalinformaticsmetabolomicsdataimportmassspectrometrybatcheffectmultiplecomparisonnormalizationqualitycontrolvisualizationpreprocessing

8.17 score 5 stars 2 packages 62 scripts 278 downloads 34 exports 56 dependencies

Last updated from:d7eaa1a10c. Checks:8 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE240
linux-devel-x86_64NOTE399
source / vignettesOK414
linux-release-x86_64NOTE351
macos-release-arm64NOTE271
macos-oldrel-arm64NOTE238
windows-develNOTE308
windows-releaseNOTE328
windows-oldrelNOTE269
wasm-releaseOK176

Exports:assess_qualitycitationscluster_featurescombined_datacompress_clusterscorrect_driftdrop_flaggeddrop_qcsfinish_logfix_MSMSfix_objectflagflag_contaminantsflag_detectionflag_qualityflag_reportflag<-import_from_excelimport_from_msdialimpute_rfimpute_simpleinit_loginverse_normalizejoin_colDatajoin_rowDatalog_textmark_nasmerge_notame_setspca_bhattacharyya_distperform_repeatabilitypqn_normalizationqualityruvs_qcwrite_to_excel

Dependencies:abindBHBiobaseBiocGenericsBiocParallelclicodetoolscpp11DelayedArraydplyrfarverformatRfutile.loggerfutile.optionsgenericsGenomicRangesggplot2gluegtableIRangesisobandlabelinglambda.rlatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsopenxlsxpillarpkgconfigpurrrR6RColorBrewerRcpprlangS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselectutf8vctrsviridisLitewithrXVectorzip

Non-targeted metabolomics preprocessing and data wrangling

Anton Klåvus, Vilhelm Suksi

Rendered fromintroduction.Rmdusingknitr::rmarkdownon May 22 2026.

Last update: 2026-01-26
Started: 2024-05-14

Project example

Anton Klåvus, Vilhelm Suksi

Rendered fromproject_example.Rmdusingknitr::rmarkdownon May 22 2026.

Last update: 2026-01-26
Started: 2019-06-19

Readme and manuals

Help Manual

Help pageTopics
'notame' package.notame-package notame
Assess quality information of featuresassess_quality
Show citationscitations
Cluster correlated features originating from the same metabolitecluster_features
Retrieve both sample information and featurescombined_data
Compress clusters of features to a single featurecompress_clusters
Correct drift using cubic splinecorrect_drift
Drop flagged featuresdrop_flagged
Drop QC samplesdrop_qcs
Finish a logfinish_log
Transform the MS/MS output to publication readyfix_MSMS
Fix object for functioning of notamefix_object
Get and set the values in the flag columnflag flag<-
Flag contaminants based on blanksflag_contaminants
Flag features with low detection rateflag_detection
Flag low-quality featuresflag_quality
A report of flagged featuresflag_report
Read formatted Excel filesimport_from_excel
Import data from a TSV file created by MS-DIALimport_from_msdial
Impute missing values using random forestimpute_rf
Simple imputationimpute_simple
Initialize log to a fileinit_log
Inverse-rank normalizationinverse_normalize
Join new columns to pheno datajoin_colData
Join new columns to feature datajoin_rowData
Log text to the current log filelog_text
Mark specified values as missingmark_nas
Merge SummarizedExperiment objects togethermerge_notame_sets
Bhattacharyya distance between batches in PCA spacepca_bhattacharyya_dist
Compute repeatability measuresperform_repeatability
Probabilistic quotient normalizationpqn_normalization
Extract quality information of featuresquality
Remove Unwanted Variation (RUV) between batchesruvs_qc
Toy data sethilic_neg_sample hilic_pos_sample rp_neg_sample rp_pos_sample toy_notame_set
Write results to Excel filewrite_to_excel