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This repository contains the codes and a tutorial for the R package "SiFINeT" v1.13.

The corresponding paper is "SifiNet: A robust and accurate method to identify feature gene sets and annotate cells".

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multiomic cellular profiles.

Please check the tutorial "SifiNet_tutorial.Rmd" for installation and a toy analysis example.

The codes to generate the analysis results in the paper can be found here.

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Version

Install

install.packages('SiFINeT')

Monthly Downloads

186

Version

1.13

License

GPL-3

Maintainer

Qi Gao

Last Published

January 16th, 2025

Functions in SiFINeT (1.13)

norm_FDR_SQAUC

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.
filter_lowexp

filter_lowexp
find_unique_feature

find_unique_feature
quantile_thres

quantile_thres
create_network

create_network
SiFINeT-class

The SiFINeT Class
cal_conn

cal_conn This function calculates the first 3 order connectivities for each gene and returns the list of vectors of connectivities.
enrich_feature_set

enrich_feature_set
cal_coexp

cal_coexp This function calculates the coexpression patterns between genes and returns the coexpression matrix.
EstNull

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.
assign_shared_feature

assign_shared_feature
cal_coexp_sp

cal_coexp_sp This function calculates the coexpression patterns between genes in sparse matrix and returns the coexpression matrix.
cal_connectivity

cal_connectivity
create_SiFINeT_object

create_SiFINeT_object
extract_subnetwork

extract_subnetwork
geneset_topology

geneset_topology
feature_coexp

feature_coexp