JiantaoShi
Computational Biology and Mathematical Modeling
Shanghai Institute of Biochemistry and Cell BiologyShanghai
Pinned Repositories
AMD
An Automated Motif Discovery Tool
AML-InVivo-CRISPR
In vivo genome-wide CRISPR screening in murine acute myeloid leukemia
bs-seq
Clipper
A p-value-free method for controlling false discovery rates in high-throughput biological data with two conditions
dit
Python package for information theory.
JiantaoShi.github.io
mTres
NetGPA
Network-based gene prioritization analysis
NetORA
Network-based pathway over-representation analysis
RegulatoryActivities
JiantaoShi's Repositories
JiantaoShi/JiantaoShi.github.io
JiantaoShi/MoranProcess
Characterizing cancer initiation by Moran Process
JiantaoShi/RegulatoryActivities
JiantaoShi/AMD
An Automated Motif Discovery Tool
JiantaoShi/AML-InVivo-CRISPR
In vivo genome-wide CRISPR screening in murine acute myeloid leukemia
JiantaoShi/bs-seq
JiantaoShi/Clipper
A p-value-free method for controlling false discovery rates in high-throughput biological data with two conditions
JiantaoShi/dit
Python package for information theory.
JiantaoShi/EPEE
Effector and Perturbation Estimation Engine (EPEE) conducts differential analysis of transcription factor activity from gene expression data.
JiantaoShi/iab2
An Introduction to Applied Bioinformatics, 2nd Edition
JiantaoShi/LSCC
Genomic landscape of somatic noncoding mutations in LSCC
JiantaoShi/mTres
JiantaoShi/NetGPA
Network-based gene prioritization analysis
JiantaoShi/NetORA
Network-based pathway over-representation analysis
JiantaoShi/IMPACT-Pipeline
Framework to process and call somatic variation from NGS dataset generated using MSK-IMPACT assay
JiantaoShi/LungMR
Master regulators in LUAD
JiantaoShi/mHapTk
JiantaoShi/mHapTools
JiantaoShi/MONOD2
MONOD2 is a toolkit for methylation haplotype analysis of bisulfite sequencing data
JiantaoShi/RIL-seq-interacting-regions
A simple tool to calculate accurate genome interacting regions based on RIL-seq
JiantaoShi/scAge
Profiling epigenetic age in single cells
JiantaoShi/single-cell-tutorial
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
JiantaoShi/TRAmHap
TRAmHap is a novel deep-learning framework, which predicts transcriptional activity using characteristics of DNA methylation haplotypes in proximal promoters and enhancers as far as 25 kb away from TSS.