Hongkai’s Research Group

Software & Database

(1) hmChIP: a database of publicly available human and mouse ChIP-seq and ChIP-chip data.

(2) PDDB:a database of predicted regulatory element activities based on BIRD

(1)    BIRD: genome-wide prediction of chromatin accessibility using RNA-seq or exon array data

(2)    CisGenome: integrated software for ChIP-seq and ChIP-chip peak calling, annotation, motif analysis, etc.

(3)    ChIP-PED: an R package with graphical user interface for discovering regulatory pathway activities  in a large compendium of gene expression data from GEO.

(4)    ChIPXpress: improve target gene ranking using gene expression information in Gene Expression Omnibus (GEO).

(5)    CorMotif: an R/bioconductor package for jointly analyzing multiple gene expression datasets to simultaneously detect differentially expression genes and patterns.

(6)    dPCA: a software tool for analyzing differential binding. It compares the quantitative ChIP-seq signals in multiple ChIP-seq datasets between two biological conditions and considers the variability in replicate samples.

(7)    GSCA: a software tool with graphical user interface for mining publicly available gene expression data. It allows one to systematically identify biological contexts associated with user-specified gene set activity patterns.

(8)    iASeq: an R/bioconductor package for detecting allele-specific binding by jointly analyzing multiple ChIP-seq data sets

(9)    JAMIE: joint analysis of multiple ChIP-chip datasets for improving peak calling.

(10)  PolyaPeak: a tool for improving ChIP-seq peak calling using peak shape information.

(11)  PowerExpress: a tool for finding genes with a user-specified pattern of interest from multiple gene expression experiments.

(12)  SCRAT: a toolbox for analyzing single-cell regulome (scATAC-seq, scDNase-seq, scChIP-seq) data.

(13)  TileMap: a software tool for ChIP-chip peak calling.

(14)  TileProbe: a software tool for removing probe effects in Affymetrix tiling array data.

(15)  TSCAN: pseudo-time analysis of single-cell RNA-seq data.