Package: smartid 1.9.0

Jinjin Chen

smartid: Scoring and Marker Selection Method Based on Modified TF-IDF

This package enables automated selection of group specific signature, especially for rare population. The package is developed for generating specifc lists of signature genes based on Term Frequency-Inverse Document Frequency (TF-IDF) modified methods. It can also be used as a new gene-set scoring method or data transformation method. Multiple visualization functions are implemented in this package.

Authors:Jinjin Chen [aut, cre]

smartid_1.9.0.tar.gz
smartid_1.9.0.zip(r-4.7)smartid_1.9.0.zip(r-4.6)smartid_1.9.0.zip(r-4.5)
smartid_1.9.0.tgz(r-4.6-any)smartid_1.9.0.tgz(r-4.5-any)
smartid_1.9.0.tar.gz(r-4.7-any)smartid_1.9.0.tar.gz(r-4.6-any)
smartid_1.9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
smartid/json (API)
NEWS

# Install 'smartid' in R:

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

Bug tracker:https://github.com/davislaboratory/smartid/issues

Pkgdown/docs site:https://davislaboratory.github.io

Datasets:

sim_sce_test - ScRNA-seq test data of 4 groups simulated by 'splatter'.

On BioConductor:smartid-1.9.0(bioc 3.24)smartid-1.8.0(bioc 3.23)

software geneexpression transcriptomics

4.30 score 1 stars 5 scripts 244 downloads 15 exports 88 dependencies

Last updated from:931d9dfb23. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	269
linux-devel-x86_64	OK	359
source / vignettes	OK	301
linux-release-x86_64	OK	310
macos-release-arm64	OK	193
macos-oldrel-arm64	OK	164
windows-devel	OK	256
windows-release	OK	246
windows-oldrel	OK	238
wasm-release	OK	190

Exports:cal_score gs_score gs_score_init idf_iae_methods markers_hdbscan markers_mclust markers_mixmdl ova_score_boxplot scale_mgm score_barplot sin_score_boxplot top_markers top_markers_abs top_markers_glm top_markers_init

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

A quick start guide to smartid: Scoring and MARker selection method based on modified Tf-IDf

Jinjin Chen

Rendered fromsmartid_Demo.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2026-04-22
Started: 2024-01-08

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
calculate combined score	cal_score cal_score,AnyMatrix-method cal_score,SummarizedExperiment-method
Calculate score for each feature in each cell	cal_score_init
compute overall score based on the given marker list	gs_score gs_score,AnyMatrix,ANY-method gs_score,AnyMatrix,list-method gs_score,SummarizedExperiment,ANY-method
Calculate scores of each cell on given features	gs_score_init
standard inverse average expression	iae
inverse average expression using hdbscan cluster as label	iae_hdb
labeled inverse average expression: IGM	iae_igm
inverse average expression: max	iae_m
labeled inverse average expression: probability based	iae_prob
labeled inverse average expression: relative frequency	iae_rf
inverse average expression using standard deviation (SD)	iae_sd
standard inverse cell frequency	idf
inverse document frequency using hdbscan cluster as label	idf_hdb
Get names of available IDF and IAE methods	idf_iae_methods
labeled inverse cell frequency: IGM	idf_igm
inverse cell frequency: max	idf_m
labeled inverse cell frequency: probability based	idf_prob
labeled inverse cell frequency: relative frequency	idf_rf
inverse cell frequency using standard deviation (SD)	idf_sd
select markers using HDBSCAN method	markers_hdbscan
select markers using mclust EM method	markers_mclust
select markers using mixtools EM method	markers_mixmdl
boxplot of features overall score	ova_score_boxplot
scale by mean of group mean for imbalanced data	scale_mgm
barplot of processed score	score_barplot
scRNA-seq test data of 4 groups simulated by 'splatter'.	sim_sce_test
boxplot of split single feature score	sin_score_boxplot
compute term/feature frequency within each cell	tf
scale score and return top markers	top_markers top_markers,AnyMatrix-method top_markers,SummarizedExperiment-method
calculate group median, MAD or mean score and order genes based on scores	top_markers_abs
calculate group mean score using glm and order genes based on scores difference	top_markers_glm
compute group summarized score and order genes based on processed scores	top_markers_init