Shen Lab at Columbia University

Computational genomics, human genetics, and computational immunology

Pinned Repositories

CANOES
Language:R8 25 02
CNV-Espresso
A tool designed for confirming copy number variants from exome sequencing predictions in silico
Language:Python5 4 00
gMVP
Language:Python20 3 06
hotspot
Language:Python5 22 01
igv-classifier
Language:HTML3 5 01
missense
MVP (Qi et al 2021) source code
Language:Jupyter Notebook15 19 09
PreMode
PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context
Language:Python4 4 01
SeqDance
code for SeqDance, a biophysics-informed protein language model
Language:Jupyter Notebook18 1 12
SPARK_Scripts
Scripts used in SPARK project
Language:Shell4 5 01
ThreaderAI
Template-based prediction of protein structure with deep-learning
Language:C++6 3 01

Shen Lab at Columbia University's Repositories

ShenLab/gMVP
Language:Python20 3 06
ShenLab/SeqDance
code for SeqDance, a biophysics-informed protein language model
Language:Jupyter Notebook18 1 12
ShenLab/missense
MVP (Qi et al 2021) source code
Language:Jupyter Notebook15 19 09
ShenLab/CANOES
Language:R8 25 02
ShenLab/ThreaderAI
Template-based prediction of protein structure with deep-learning
Language:C++6 3 01
ShenLab/CNV-Espresso
A tool designed for confirming copy number variants from exome sequencing predictions in silico
Language:Python5 4 00
ShenLab/PreMode
PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context
Language:Python4 4 01
ShenLab/SPARK_Scripts
Scripts used in SPARK project
Language:Shell4 5 01
ShenLab/episcore
Language:R3 13 02
ShenLab/igv-classifier
Language:HTML3 5 01
ShenLab/MisFit
Estimation of selection coefficient of missense variants using human population genomes and machine learning
Language:Python3 2 00
ShenLab/AlphaCluster
quantify 3D physical or functional clustering of missense variants
Language:Python2 5 00
ShenLab/pipeline
Language:Python2 24 01
ShenLab/SPARK_Analysis_V1
Language:Perl2 4 01
ShenLab/A-risk
F-risk, plausibility of risk genes of autism
Language:Jupyter Notebook1 15 01
ShenLab/biocluster
Tutorial on building a computing cluster for bioinformatics
1 4 0
ShenLab/Genetics
Language:Python1 24 04
ShenLab/mosaicism
Language:R1 18 01
ShenLab/noncoding
Predict site-specific RNA binding protein - mRNA binding and functional impact of noncoding variants based on RBP binding and population genomes.
Language:R1 21 0
ShenLab/rescve
Representation of missense variants for predicting modes of action
Language:Python1 2 00
ShenLab/VariableThresholdTest
Language:Perl1 3 0
ShenLab/VBASS
A Bayesian Mixture model with learnable prior to integrate single cell gene expression data in rare variants association analysis.
Language:R1 3 0
ShenLab/viralTCR
A machine learning method to predict TCR-peptide binding
Language:Python1 2 00
ShenLab/spark
SPARK and genetics analysis of ASD
Language:Perl0 5 01
ShenLab/TCR
Language:Jupyter Notebook0 26 06
ShenLab/lollipop
3 0
ShenLab/pathways
Pathway enrichment analysis of de novo or rare variants.
Language:R3 0
ShenLab/shenlab.github.io
large files (PDF or images) for Shen Lab
4 0
ShenLab/US_UK_combine
Language:R2 0
ShenLab/x-TADA
A new model to integrate functional genomics data in identifying de novo risk genes.
Language:R3 0