Package: SiFINeT 1.13

Qi Gao

SiFINeT: Single Cell Feature Identification with Network Topology

Cluster-independent method based on topology structure of gene co-expression network for identifying feature gene sets, extracting cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Without prior cell clustering, SifiNet circumvents potential inaccuracies in clustering that may influence subsequent analyses. This method is introduced in Qi Gao, Zhicheng Ji, Liuyang Wang, Kouros Owzar, Qi-Jing Li, Cliburn Chan, Jichun Xie "SifiNet: a robust and accurate method to identify feature gene sets and annotate cells" (2024) <doi:10.1093/nar/gkae307>.

Authors:Qi Gao [aut, cre]

SiFINeT_1.13.tar.gz
SiFINeT_1.13.tar.gz(r-4.5-noble)SiFINeT_1.13.tar.gz(r-4.4-noble)
SiFINeT_1.13.tgz(r-4.4-emscripten)SiFINeT_1.13.tgz(r-4.3-emscripten)
SiFINeT.pdf |SiFINeT.html✨
SiFINeT/json (API)
NEWS

# Install 'SiFINeT' in R:
install.packages('SiFINeT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

2.85 score 14 scripts 208 downloads 15 exports 58 dependencies

Last updated 1 months agofrom:2981dc1586. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 15 2025
R-4.5-linux-x86_64OKFeb 15 2025

Exports:assign_shared_featurecal_coexpcal_coexp_spcal_connectivitycreate_networkcreate_SiFINeT_objectenrich_feature_setEstNullextract_subnetworkfeature_coexpfilter_lowexpfind_unique_featuregeneset_topologynorm_FDR_SQAUCquantile_thres

Dependencies:cachemclicolorspacecpp11dplyrfansifarverfastmapgenericsggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmemoisemgcvmunsellnlmepillarpkgconfigpolyclippurrrquantregR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesSparseMstringistringrsurvivalsystemfontstibbletidygraphtidyrtidyselecttweenrutf8vctrsviridisviridisLitewithr

Introduction to SifiNet

Qi Gao

Rendered fromSifiNet_tutorial.Rmdusingknitr::rmarkdownon Feb 15 2025.

Last update: 2025-01-16
Started: 2025-01-16

Readme and manuals

Help Manual

Help pageTopics
assign_shared_featureassign_shared_feature
cal_coexp This function calculates the coexpression patterns between genes and returns the coexpression matrix.cal_coexp
cal_coexp_sp This function calculates the coexpression patterns between genes in sparse matrix and returns the coexpression matrix.cal_coexp_sp
cal_conn This function calculates the first 3 order connectivities for each gene and returns the list of vectors of connectivities.cal_conn
cal_connectivitycal_connectivity
create_networkcreate_network
create_SiFINeT_objectcreate_SiFINeT_object
enrich_feature_setenrich_feature_set
EstNull This function is a Rcpp version of Wenguang Sun and Tony T. Cai's EstNull.func R function, estimating null distribution from data. Sun, W., & Cai, T. T. (2007). Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control. Journal of the American Statistical Association, 102(479), 901–912.EstNull
extract_subnetworkextract_subnetwork
feature_coexpfeature_coexp
filter_lowexpfilter_lowexp
find_unique_featurefind_unique_feature
geneset_topologygeneset_topology
norm_FDR_SQAUC The function controls the false discovery rate (FDR) of coexpression patterns using SQAUC method Jichun Xie and Ruosha Li. "False discovery rate control for high dimensional networks of quantile associations conditioning on covariates". In: J R Stat Soc Series B Stat Methodol (2018). doi: 10.1111/rssb.12288.norm_FDR_SQAUC
quantile_thresquantile_thres
The SiFINeT ClassSiFINeT SiFINeT-class