Package: sfi 1.1.0

Miao YU

sfi: Data analysis for Single File Injections (SFIs) mode LC-MS analysis

Data analysis for Single File Injections(SFIs) mode LC-MS analysis. In SFIs mode, pooled samples are initially injected to serve as reference peaks for subsequent analyses. Repeated injections of individual samples are then performed at fixed time intervals using isocratic elution. This package provides the functions to analyze data from SFIs mode including peak picking and peak reassignment.

Authors:Miao YU [aut, cre]

sfi_1.1.0.tar.gz
sfi_1.1.0.zip(r-4.7)sfi_1.1.0.zip(r-4.6)sfi_1.1.0.zip(r-4.5)
sfi_1.1.0.tgz(r-4.6-x86_64)sfi_1.1.0.tgz(r-4.6-arm64)sfi_1.1.0.tgz(r-4.5-x86_64)sfi_1.1.0.tgz(r-4.5-arm64)
sfi_1.1.0.tar.gz(r-4.7-arm64)sfi_1.1.0.tar.gz(r-4.7-x86_64)sfi_1.1.0.tar.gz(r-4.6-arm64)sfi_1.1.0.tar.gz(r-4.6-x86_64)
sfi_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sfi/json (API)
NEWS

# Install 'sfi' in R:

install.packages('sfi', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yufree/sfi/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

sfi - Demo sfi data

On BioConductor:sfi-1.1.0(bioc 3.24)sfi-1.0.0(bioc 3.23)

massspectrometry metabolomics featureextraction cpp

4.70 score 1 stars 5 scripts 174 downloads 10 exports 101 dependencies

Last updated from:d517312814. Checks:1 NOTE, 13 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	289
linux-devel-arm64	OK	359
linux-devel-x86_64	OK	452
source / vignettes	OK	318
linux-release-arm64	OK	361
linux-release-x86_64	OK	430
macos-release-arm64	OK	315
macos-release-x86_64	OK	543
macos-oldrel-arm64	OK	203
macos-oldrel-x86_64	OK	651
windows-devel	OK	308
windows-release	OK	404
windows-oldrel	OK	294
wasm-release	OK	219

Exports:find_2d_peaks find_peaks_low_res get_qc_features get_sfi_params getidelta getmzml getsff getsfm getwindow run_app

Dependencies:abind animation askpass base64enc BH Biobase BiocGenerics BiocParallel bslib cachem cli codetools cpp11 crosstalk curl data.table DelayedArray digest dplyr enviGCMS evaluate farver fastmap fontawesome formatR fs futile.logger futile.options generics GenomicRanges ggplot2 glue gtable highr htmltools htmlwidgets httr igraph IRanges isoband jquerylib jsonlite kernlab knitr labeling lambda.r later lattice lazyeval lifecycle magick magrittr MASS Matrix MatrixGenerics matrixStats memoise mime mixtools nlme openssl otel pillar pkgconfig plotly promises purrr R6 RaMS rappdirs RColorBrewer Rcpp Rdisop rlang rmarkdown S4Arrays S4Vectors S7 sass scales segmented Seqinfo snow SparseArray stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun xml2 XVector yaml

sfi workflow

Rendered fromworkflow.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2026-06-11
Started: 2025-05-28

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Feature extraction core function	find_2d_peaks
Find peaks in low-resolution data using the 2D peak finding algorithm	find_peaks_low_res
Generate Quality Control Feature List	get_qc_features get_qc_features.default get_qc_features.sfi_peaks
Quality Control for Mass Spectrometry Data	get_sfi_params get_sfi_params.default get_sfi_params.sfi_peaks
Optimize Delta Retention Time	getidelta getidelta.default getidelta.sfi_peaks
Read mzML File and Extract m/z, Retention Time, and Intensity	getmzml
Cluster and Pair m/z and Retention Time Features	getsff getsff.default getsff.sfi_peaks
Generate Sample Feature Matrix (SFM)	getsfm getsfm.default getsfm.sfi_peaks
Determine Optimal Retention Time Window	getwindow getwindow.default getwindow.sfi_peaks
Run sfi Shiny App	run_app
Demo sfi data	sfi