call.npci | the s4 class function |
call.npci-method | ~~ Methods for Function 'call.npci' ~~ |
call.npci-methods | ~~ Methods for Function 'call.npci' ~~ |
compute | the generic function 'compute' for s4 class |
compute-method | ~~ Methods for Function 'compute' ~~ |
compute-methods | ~~ Methods for Function 'compute' ~~ |
deg.pairwise.fold.change | find targets that have a consistent fold change in the same direction (either up- or down-regulation) |
deg.up.down.info | find targets and their detailed expression changes |
deseq.median.ratio.normalization | data matrix normalization method |
divergence.multivariate.distributions | estimate fCI divergence for given samples of aritrary dimensions |
fCI-class | Class '"fCI"' |
fCI.call.by.index | top level function call to find targets based on expression data and control & case indexes |
fci.data | data frame of gene expression |
figures | generic function to draw figures of the current analysis |
figures-method | generate figures for empirical null and case-control distributions |
figures-methods | generate figures for empirical null and case-control distributions |
find.fci.targets | identify differentially expressed genes |
find.mid.point | find the middle value of the density distribution |
get.fold.large.step | generate fold change cutoff values for fCI divergence computation |
get.npci.data | return a fCI object given the gene expression data |
get.npci.distance.matrix | generate the divergence estimation based of fold change cutoff values |
get.outline.index | find the outline genes of a given distribution |
get.protein.fold.step | generate fold-change cutoff on proteomics data (with large steps of 0.2-0.5 fold) |
get.rank.combinations | fold change values |
get.rna.fold.step | generate fCI fold-change cutoff values for typical RNA-Seq data |
initialize-method | ~~ Methods for Function 'initialize' ~~ |
initialize-methods | ~~ Methods for Function 'initialize' ~~ |
intersect.of.lists | find the common values of all vectors of a list |
is.installed | package |
multi.dimensional.fci.data | data frame of gene expression |
normalization | generic function to normalize gene expression matrix |
normalization-method | ~~ Methods for Function 'normalization' ~~ |
normalization-methods | ~~ Methods for Function 'normalization' ~~ |
npci.gene.by.pvalues | find most signficantly change fCI targets |
npci.index.reconsidered | find targets that have little evidence to be differentially expressed |
npci.index.to.be.removed | gene indexes that will be considered as targets |
npci.venn.diagram | generate venn diagram for multiple fCI analysis |
pairwise.change.occupancy | find the targets whose fold changes occur consistently (upregulated or downregulated) in all fCI analysis |
populate | generic function to populate the fCI object based on provided data |
populate-method | ~~ Methods for Function 'populate' ~~ |
populate-methods | ~~ Methods for Function 'populate' ~~ |
report.target.summary | generate the results (gene ids) in the data frame |
show.targets | display the gene ids that are identified to be differentially regulated |
summarize | result summerization |
summarize-method | result summerization |
summarize-methods | result summerization |
total.library.size.normalization | normalize the gene expression based on the library size (summation) of the first sample replicate |
trim.size.normalization | normalize gene expression by exluding genes on the top 5 and bottom 5 percentage |
two.sample.log.ratio | compute the log ratios of two vectors |
two.sample.permutation.test | perform permuation test on two vectors |
venndiagram | generate a venn diagram to show the differentially expression summaries accross pairwise fCI analysis |
venndiagram-method | ~~ Methods for Function 'venndiagram' ~~ |
venndiagram-methods | ~~ Methods for Function 'venndiagram' ~~ |