wu-yc

wu-yc's Stars

• DongqiangZeng0808/TMEscore

  Calculating Tumor microenvironment score

  Language:R2710

• statbiophys/SONIA

  Infer selection pressures on features of amino acid CDR3 sequences.

  Language:Python237

• statbiophys/soNNia

  Language:Python134

• sankaranlab/SCAVENGE

  SCAVENGE is a method to optimize the inference of functional and genetic associations to specific cells at single-cell resolution.

  Language:R7734

• saezlab/liana

  LIANA: a LIgand-receptor ANalysis frAmework

  Language:R17531

• mainciburu/WAT3R

  Workflow for the Association of T-cell receptors from 3' single-cell RNA-seq (WAT3R)

  Language:R212

• molgenis/1M-cells

  This is the repository which contains the code that was used to generate the results and figures of the “Single-cell RNA-sequencing reveals widespread personalized, context-specific gene expression regulation in immune cells” paper (https://doi.org/10.1038/s41467-022-30893-5)

  Language:R10

• jokergoo/simplifyEnrichment

  Simplify functional enrichment results

  Language:R10816

• PKUFlyingPig/cs-self-learning

  计算机自学指南

  Language:HTML56.3k6.8k

• Camp-Lab/human_endoderm_atlas

  Language:R82

• livnatje/DIALOGUE

  DIALOGUE is a dimensionality reduction method that uses cross-cell-type associations to identify multicellular programs (MCPs) and map the cell transcriptome as a function of its environment.

  Language:R10216

• pinellolab/STREAM

  STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of single-cell data

  Language:Jupyter Notebook17346

• martinjzhang/scDRS

  Single-cell disease relevance score (scDRS)

  Language:Jupyter Notebook10814

• openvax/mhctools

  Python interface to running command-line and web-based MHC binding predictors

  Language:Python8921

• GfellerLab/MixMHC2pred

  HLA-II ligand predictor.

  Language:C++3410

• delosh653/ECHO

  An application to find and visualize circadian rhythms in time course data using extended harmonic oscillators.

  Language:R13

• zhengrongbin/MEBOCOST

  A python-based package and software to predict metabolite mediated cell-cell communications by single-cell RNA-seq data

  Language:Jupyter Notebook6310

• derekbeaton/GSVD

  Language:R196

• emmijokinen/TCRconv

  TCRconv is a deep learning model for predicting recognition between T cell receptors and epitopes. It uses protBERT embeddings for the TCRs and convolutional neural networks for the prediction.

  Language:Jupyter Notebook226

• immunogenomics/LISI

  Methods to compute Local Inverse Simpson's Index (LISI)

  Language:R565

• mw201608/msigdb

  MSigDB gene sets

  Language:R53

• immunogenomics/TiRP

  code repository for Lagattuta et al. "Repertoire analyses reveal T cell receptor sequence features that influence T cell fate." Nat. Imm. (2022)

  Language:Jupyter Notebook115

• jcao89757/TESSA

  Mapping the Functional Landscape of TCR Repertoire

  Language:R337

• IdoSpringer/ERGO-II

  ERGO-II, an updated version of ERGO including more features for TCR-peptide binding prediction

  Language:Python296

• mnielLab/NetTCR-2.0

  NetTCR-2.0. Sequence-based prediction of peptide-TCR binding

  Language:Python3310

• SeojinBang/TCR

  TCR to epitope binding prediction approach using VIBI

  Language:Python11

• umccr/neoantigens

  🏺 Exploring novel tumor epitope identification

  Language:Python3510

• im3sanger/dndscv

  dN/dS methods to quantify selection in cancer and somatic evolution

  Language:HTML21148

• luisgls/dNdSSimulator

  dNdS Simulator uses R to simulate a stochastic branching process with a set of genotypes and phenotypes per cell. The main advantage of the model is that simulates immunoediting by introducing immunogenic and escape mutations as well as driver and passenger mutations

  Language:HTML21

• luisgls/SOPRANO

  SelectiOn in PRotein ANnotated regiOns. Adapted dN/dS based method to detect selection in specific protein regions

  Language:Perl112