Package: SGCP 1.7.0

Niloofar AghaieAbiane

SGCP: SGCP: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks

SGC is a semi-supervised pipeline for gene clustering in gene co-expression networks. SGC consists of multiple novel steps that enable the computation of highly enriched modules in an unsupervised manner. But unlike all existing frameworks, it further incorporates a novel step that leverages Gene Ontology information in a semi-supervised clustering method that further improves the quality of the computed modules.

Authors:Niloofar AghaieAbiane [aut, cre], Ioannis Koutis [aut]

SGCP_1.7.0.tar.gz
SGCP_1.7.0.zip(r-4.5)SGCP_1.7.0.zip(r-4.4)SGCP_1.7.0.zip(r-4.3)
SGCP_1.7.0.tgz(r-4.4-any)SGCP_1.7.0.tgz(r-4.3-any)
SGCP_1.7.0.tar.gz(r-4.5-noble)SGCP_1.7.0.tar.gz(r-4.4-noble)
SGCP_1.7.0.tgz(r-4.4-emscripten)SGCP_1.7.0.tgz(r-4.3-emscripten)
SGCP.pdf |SGCP.html✨
SGCP/json (API)
NEWS

# Install 'SGCP' in R:

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

Bug tracker:https://github.com/na396/sgcp/issues

Datasets:

cheng - Normalized gene expression data from Cheng et al.'s publication on ischemic cardiomyopathy (ICM).
resClus - An example of the output from 'clustering' function in the SGCP pipeline
resFinalGO - An example of the output from 'geneOntololgy' function in the SGCP pipeline
resInitialGO - An example of the output from the 'geneOntololgy' function in the SGCP pipeline
resSemiLabel - An example of the output from 'semiLabeling' function in the SGCP pipeline
resSemiSupervised - An example of the output from 'semiSupervised' function in the SGCP pipeline
sgcp - An example of the output of 'ezSGCP' function in the SGCP pipeline

On BioConductor:SGCP-1.7.0(bioc 3.21)SGCP-1.6.0(bioc 3.20)

geneexpression genesetenrichment networkenrichment systemsbiology classification clustering dimensionreduction graphandnetwork neuralnetwork network mrnamicroarray rnaseq visualization bioinformatics genecoexpressionnetwork graphs networkclustering networks self-training semi-supervised-learning unsupervised-learning

5.12 score 2 stars 44 scripts 245 downloads 15 exports 154 dependencies

Last updated 2 months agofrom:ba0ddcc40f. Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 18 2024
R-4.5-win	NOTE	Dec 18 2024
R-4.5-linux	NOTE	Dec 18 2024
R-4.4-win	NOTE	Dec 18 2024
R-4.4-mac	NOTE	Dec 18 2024
R-4.3-win	OK	Dec 18 2024
R-4.3-mac	OK	Dec 18 2024

Exports:adjacencyMatrix clustering ezSGCP geneOntology semiLabeling semiSupervised SGCP_ezPLOT SGCP_plot_bar SGCP_plot_conductance SGCP_plot_density SGCP_plot_heatMap SGCP_plot_jitter SGCP_plot_pca SGCP_plot_pie SGCP_plot_silhouette

Dependencies:abind annotate AnnotationDbi AnnotationForge askpass BH Biobase BiocGenerics Biostrings bit bit64 bitops blob boot cachem caret Category cellranger class cli clipr clock codetools colorspace cpp11 crayon curl data.table DBI DelayedArray DescTools diagram digest dplyr e1071 Exact expm fansi farver fastmap forcats foreach future future.apply genefilter generics GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 ggridges gld globals glue GO.db GOstats gower graph GSEABase gtable hardhat haven hms httr ipred IRanges isoband iterators jsonlite KEGGREST KernSmooth labeling lattice lava lifecycle listenv lmom lubridate magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime ModelMetrics munsell mvtnorm nlme nnet numDeriv openssl openxlsx org.Hs.eg.db parallelly pillar pkgconfig plogr plyr png prettyunits pROC prodlim progress progressr proxy purrr R6 RBGL RColorBrewer Rcpp RcppEigen RCurl readr readxl recipes rematch reshape2 Rgraphviz rlang rootSolve rpart RSpectra RSQLite rstudioapi S4Arrays S4Vectors scales shape SparseArray SQUAREM stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect timechange timeDate tzdb UCSC.utils utf8 vctrs viridisLite vroom withr XML xtable XVector zip zlibbioc

SGCP package manual

Niloofar Aghaieabiane

Rendered fromSGCP.Rmdusingknitr::rmarkdownon Dec 18 2024.

Last update: 2024-06-29
Started: 2022-10-14

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Performs netwrok construction step in the SGCP pipeline	adjacencyMatrix
Normalized gene expression data from Cheng et al.'s publication on ischemic cardiomyopathy (ICM).	cheng
Perform network clustering step in the SGCP pipeline	clustering
Integrated execution of the SGCP pipeline	ezSGCP
Performs gene ontology enrichment step in the SGCP pipeline.	geneOntology
An example of the output from 'clustering' function in the SGCP pipeline	resClus
An example of the output from 'geneOntololgy' function in the SGCP pipeline	resFinalGO
An example of the output from the 'geneOntololgy' function in the SGCP pipeline	resInitialGO
An example of the output from 'semiLabeling' function in the SGCP pipeline	resSemiLabel
An example of the output from 'semiSupervised' function in the SGCP pipeline	resSemiSupervised
Performs gene semi-labeling step in the SGCP pipeline	semiLabeling
Performs the semi-supervised step in the SGCP pipeline	semiSupervised
An example of the output of 'ezSGCP' function in the SGCP pipeline	sgcp
Comprehensive SGCP plotting in one execution	SGCP_ezPLOT
Mean p-value bar chart for gene ontology enrichment in the SGCP pipeline	SGCP_plot_bar
Cluster conductance index bar chart in the SGCP Pipeline	SGCP_plot_conductance
Visualization of gene ontology term p-value distribution in the SGCP pipeline	SGCP_plot_density
Adjacency matrix heatmap in the SGCP pipeline	SGCP_plot_heatMap
P-value jitter chart for gene ontology enrichment in the SGCP pipeline.	SGCP_plot_jitter
PCA visualization in the SGCP Pipeline	SGCP_plot_pca
Gene ontology analysis pie chart in the SGCP pipeline	SGCP_plot_pie
Cluster silhouette index chart in the SGCP Pipeline	SGCP_plot_silhouette