Package: DNLC 1.0.0
DNLC: Differential Network Local Consistency Analysis
Using Local Moran's I for detection of differential network local consistency.
Authors:
DNLC_1.0.0.tar.gz
DNLC_1.0.0.zip(r-4.5)DNLC_1.0.0.zip(r-4.4)DNLC_1.0.0.zip(r-4.3)
DNLC_1.0.0.tgz(r-4.4-any)DNLC_1.0.0.tgz(r-4.3-any)
DNLC_1.0.0.tar.gz(r-4.5-noble)DNLC_1.0.0.tar.gz(r-4.4-noble)
DNLC_1.0.0.tgz(r-4.4-emscripten)DNLC_1.0.0.tgz(r-4.3-emscripten)
DNLC.pdf |DNLC.html✨
DNLC/json (API)
# Install 'DNLC' in R: |
install.packages('DNLC', repos = c('https://yushengding.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:a471544877. Checks:OK: 1 WARNING: 1 NOTE: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-win | NOTE | Nov 16 2024 |
R-4.5-linux | WARNING | Nov 16 2024 |
R-4.4-win | NOTE | Nov 16 2024 |
R-4.4-mac | NOTE | Nov 16 2024 |
R-4.3-win | NOTE | Nov 16 2024 |
R-4.3-mac | NOTE | Nov 16 2024 |
Exports:cal_lmi_dataDNLC_statisticsgene_fdrtestinit_simulation_gene_netsignificant_genes
Dependencies:annotateAnnotationDbiAnnotationForgeaskpassBHBiobaseBiocGenericsBiostringsbitbit64bitopsblobbootcachemCategorycaToolsclassclassIntclicpp11crayoncurlDBIdeldire1071fastmapfdrtoolgenefiltergenericsGenomeInfoDbGenomeInfoDbDataglueGO.dbGOstatsgraphGSEABasehttrigraphIRangesjsonliteKEGGRESTKernSmoothlatticelifecyclelocfdrmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimemvtnormopensslpkgconfigplogrpngproxyR6RBGLRcppRCurlRgraphvizrlangRSQLites2S4VectorssfspspDataspdepsurvivalsysUCSC.utilsunitsvctrswkXMLxtableXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Calculate local moran's I matrix for a network and a gene expression matrix | cal_lmi_data |
calculate t statistics for gene graph using DNLC method. | DNLC_statistics |
Use local false discovery rate for the detection of genes with significant LMI change | gene_fdrtest |
Create a random network for simulation | init_simulation_gene_net |
Selecting significant genes according to fdr result | significant_genes |