gene-expression

There are 404 repositories under gene-expression topic.

  • seandavi/awesome-single-cell

    Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

    3.3k24823995

  • COMBINE-lab/salmon

    🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment

    Language:C++78038839164

  • saeyslab/nichenetr

    NicheNet: predict active ligand-target links between interacting cells

    Language:R50114289119

  • lucidrains/enformer-pytorch

    Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

    Language:Python441173884

  • broadinstitute/Tangram

    Spatial alignment of single cell transcriptomic data.

    Language:Jupyter Notebook263139251

  • junjunlab/ClusterGVis

    One-step to Cluster and Visualize Gene Expression Matrix

    Language:R256410125

  • iSEE/iSEE

    R/shiny interface for interactive visualization of data in SummarizedExperiment objects

    Language:R2251820842

  • greenelab/tybalt

    Training and evaluating a variational autoencoder for pan-cancer gene expression data

    Language:HTML165104362

  • uci-cbcl/D-GEX

    Deep learning for gene expression inference

    Language:Python14721957

  • fbrundu/pymrmr

    Python3 binding to mRMR Feature Selection algorithm (currently not maintained)

    Language:C++13823237

  • saezlab/dorothea

    R package to access DoRothEA's regulons

    Language:R136154827

  • federicomarini/awesome-expression-browser

    😎 A curated list of software and resources for exploring and visualizing (browsing) expression data 😎

    13216238

  • greenelab/pancancer

    Building classifiers using cancer transcriptomes across 33 different cancer-types

    Language:Jupyter Notebook120102057

  • Adibvafa/CodonTransformer

    CodonTransformer: The ultimate tool for codon optimization, optimizing DNA sequences for heterologous protein expression across 164 species.

    Language:Python1092104

  • bvieth/powsimR

    Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

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  • catavallejos/BASiCS

    BASiCS: Bayesian Analysis of Single-Cell Sequencing Data. This is an unstable experimental version. Please see http://bioconductor.org/packages/BASiCS/ for the official release version

    Language:R84717017

  • nunofonseca/irap

    integrated RNA-seq Analysis Pipeline

    Language:R83156635

  • lucidrains/tf-bind-transformer

    A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

    Language:Python82809

  • GfellerLab/EPIC

    Repository for the R package EPIC, to Estimate the Proportion of Immune and Cancer cells from bulk gene expression data.

    Language:R7751421

  • federicomarini/GeneTonic

    Enjoy your transcriptomic data and analysis responsibly - like sipping a cocktail

    Language:R766258

  • helicalAI/helical

    This repository contains the python package for Helical

    Language:Python71317

  • aertslab/SCope

    Fast visualization tool for large-scale and high dimensional single-cell data

    Language:Python68934715

  • greenelab/BioBombe

    BioBombe: Sequentially compressed gene expression features enhances biological signatures

    Language:Jupyter Notebook6465425

  • JEFworks-Lab/MERINGUE

    characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities

    Language:R634155

  • AAlhendi1707/countToFPKM

    Convert Counts to Fragments per Kilobase of Transcript per Million (FPKM)

    Language:R6231215

  • greenelab/adage

    Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016

    Language:Python6115030

  • COMBINE-lab/terminus

    Language:Rust576113

  • uc-bd2k/GREIN

    GREIN : GEO RNA-seq Experiments Interactive Navigator

    Language:HTML4872919

  • andymckenzie/DGCA

    Differential Gene Correlation Analysis

    Language:R4641510

  • pinellolab/haystack_bio

    Haystack: Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline

    Language:HTML464711

  • gaolabtools/scNanoGPS

    Single cell Nanopore sequencing data for Genotype and Phenotype

    Language:Python425434

  • SUwonglab/PECA

    PECA is a software for inferring context specific gene regulatory network from paired gene expression and chromatin accessibility data

    Language:MATLAB425146

  • drostlab/myTAI

    Evolutionary Transcriptomics with R

    Language:R4161718

  • jasdumas/shinyGEO

    Gene Expression Omnibus Analysis with Shiny :microscope:

    Language:CSS4173647

  • ezgisubasi/breast-cancer-gene-expression

    This project aims to predict people who will survive breast cancer using machine learning models with the help of clinical data and gene expression profiles of the patients.

    Language:Jupyter Notebook38404

  • nuno-agostinho/psichomics

    Interactive R package to quantify, analyse and visualise alternative splicing

    Language:R36537911