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Gerstein Lab's Projects

gram icon gram

GRAM: A GeneRAlized Model to predict the molecular effect of a non-coding variant in a cell type-specific manner

hic-spector icon hic-spector

Spectral and reproducibility analysis of Hi-C contact maps

idash22bc icon idash22bc

Solution to track 1 of iDASH 2022 secure genome analysis competition

idash23bc icon idash23bc

Solution to Track 2 of the 2023 iDASH competition

intensification icon intensification

The package includes the MotifVar pipeline developed in the Gerstein Lab at Yale for the Intensification resource. This pipeline was used to generate SNV population-genetic profiles using a variety of public data sources, including SMART domain database, ExAC, Ensembl and VEP. Please see website for more detailed README. This is a SEMI-automated pipeline, where possible manual work can be done on a small number of modules to make your analyses more accurate or specific to your needs. These modules are highlighted in the README and motifvar.sh wrapper with -m.

iqseq icon iqseq

Isoform quantification from RNA-seq data

larva icon larva

Large-scale Analysis of Recurrent Variants in noncoding Annotations

lesseq icon lesseq

Local Event-based analysis of alternative Splicing using RNA-Seq

logit-fit icon logit-fit

Logistic regression fitting code designed for use with CUDA. Rather than speeding up the running time of a single regression, the code performs the regression in parallel on hundreds of samples.

matchedfilter icon matchedfilter

Prediction of Active Enhancers and Promoters in a Cell type specific manner using shape matching of histone and/or DNase-I hypersensitivity profiles

ml-bench icon ml-bench

The Official Repo of ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code (https://arxiv.org/abs/2311.09835)

moat icon moat

Mutations Overburdening Annotations Tool

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