riverlee/hg19_mRNA-lncRNA
Gene annotation containing RefSeq gene + lncRNA genes from gencode +
Developer Profile
riverlee
Discovered public repositories for riverlee in the GitHub catalog.
riverlee/FOTCL
Feature Occupancy Transition between Cell Lines (FOTCL)
riverlee/orolab
Public repository.
riverlee/reports
An R package to assist in the workflow of writing academic articles and other reports
riverlee/Personal
Personal code
riverlee/perldoc-vim
Perldoc plugin for vim
riverlee/IgeRNA
Inducing gene expression by guided RNA
riverlee/IeRNA
Identify eRNA
riverlee/CQScripts
A collection of scripts when I worked at Vanderbilt
riverlee/IntronGTF
Make a Intron GTF file from a bed
riverlee/PkgControl
A mixture scripts of perl and shell to control the package between different version
riverlee/genbank2gtf
Public repository.
riverlee/MitoSeek
Seeking information like heteroplasmy, structure variants, etc. on Mitochondrial genome from next generation sequencing
riverlee/DO.db
Scripts to build up DO.db package based on a obo file
riverlee/seqscripts
Scripts for parsing the output from the Tophat/Cufflinks/Cuffcompare pipeline into other formats and analyzing and editing GTF files.
riverlee/NGScripts
A collection of scripts for NGS data analysis
riverlee/viewFusion
View fusion event by circos plot
riverlee/knitr
A general-purpose tool for dynamic report generation in R
riverlee/pileup2base
Parse samtools pileup file to get how many bases and what kind of bases are called
riverlee/RNASeqDEPipeline
RNA-Seq differential gene expression pipeline
riverlee/miRNA-SNP
The code is to get SNPs located in miRNA/pre-miRNA and their relationship(in loop, upstream of miRNA, downstream of miRNA, seed region or just in the miRNA) miRNA data is from mirBase while dbSNP data is from vcf file
riverlee/DOSim
DOSim is developed on DO to 1) measure the similarity between diseases (DO terms), 2) measure the similarity between human genes in terms of diseases, 3) detect DO-driven gene modules and multilayer annotate them on dieases (DO), functions(GO) and pathways(KEGG), 4) conduct DO enrichment analysis, and 5) visualize and describe DO structures and terms. It focuses on the computation of disease similarity and gene similarity. Besides, its module detection and annotation would promote our understanding of the complex pathogenesis of diseases.