f6v

f6v's Stars

• lh3/seqtk

  Toolkit for processing sequences in FASTA/Q formats

  Language:C1.4k62173308

• duerrsimon/bioicons

  A library of free open source icons for science illustrations in biology and chemistry

  Language:Vue1.3k174475

• hrbrmstr/hrbrthemes

  :lock_with_ink_pen: Opinionated, typographic-centric ggplot2 themes and theme components

  Language:R1.2k244796

• jespermaag/gganatogram

  Create anatograms using ggplot2

  Language:R38292752

• smorabit/hdWGCNA

  High dimensional weighted gene co-expression network analysis

  Language:R352530635

• openproblems-bio/openproblems

  Formalizing and benchmarking open problems in single-cell genomics

  Language:Python316718479

• swaruplab/Single-nuclei-epigenomic-and-transcriptomic-landscape-in-Alzheimer-disease

  Single-nuclei RNA-seq and ATAC-seq in Alzheimer's disease

  Language:R8311231

• cssmillie/ulcerative_colitis

  Language:R573927

• berenslab/umi-normalization

  Companion repository to Lause, Berens & Kobak (2021): "Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data", Genome Biology

  Language:Jupyter Notebook41832

• bicycle1885/CellFishing.jl

  Fast and scalable cell search tool

  Language:Julia41747

• GreiffLab/immuneSIM

  Language:R38235

• ttgump/scDeepCluster_pytorch

  Pytorch implementation of scDeepCluster for Single Cell RNA-seq data

  Language:Jupyter Notebook31154

• xinyu-dev/igblast

  Detailed explanation on how to setup database for NCBI IgBlast executable, and using it in Python

  Language:Jupyter Notebook28154

• immunogenomics/amp_phase1_ra

  :ear_of_rice: Zhang, et al, Nature Immunology, 2019. Use single-cell transcriptomics and proteomics to study autoimmune diseases.

  Language:Jupyter Notebook217113

• eddiecg/T-cell-effectorness

  Codes used for all the data analysis steps in the paper "Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4+ T cells to cytokines"

  Language:R17101

• yeee904/RA_scRNA

  Rheumatoid Arthritis project. single cell RNA sequencing data.

  Language:R14124

• lmassier/hWAT_singlecell

  meta-analysis of new and published human WAT single cell data

  Language:R12210

• niaid/baseline

  Reproducible workflows for the data analysis of "Baseline" project

  Language:HTML10636

• cew88/AutoCAT

  Language:Python9104

• greenelab/CZI-Latent-Assessment

  Supplement to the report in https://greenelab.github.io/czi-hca-report/

  Language:R9712

• satijalab/seurat-docker

  Docker images of Seurat

  Language:Dockerfile8527

• twclab/parabiosis

  Jupyter notebooks describing downstream computational analyses of "Molecular hallmarks of heterochronic parabiosis at single cell resolution"

  Language:Jupyter Notebook6110

• felixhorns/SingleBCell-FluVaccine

  Analysis of single-cell and repertoire sequencing for Horns et al. Cell Reports 2020

  Language:Jupyter Notebook5401

• GabrielBalabanResearch/TCRpower

  Power calculator for determining the minimum number of reads and sampled cells needed to detect a rare T-cell clonotype from receptor sequencing.

  Language:Jupyter Notebook4101

• jsilve24/zero_types_paper

  Code to reproduce analysis and figures in the Zero Types Paper

  Language:R4402

• samuel-marsh/Marsh_et-al_2022_scRNAseq_Dissociation_Artifacts

  Code to reproduce analysis objects for the data contained in Marsh et al., 2022

  Language:R4112

• NobodyXu/intel-mkl-docker

  Docker image that has intel-mkl installed. Provides debian:buster and ubuntu:bionic based images on docker hub.

  Language:Dockerfile321

• wangxiaoman618/BD_project

  Language:R3101

• Weng-lab-NIH/CD8_aging_figure_scripts

  Figure Scripts for the healthy CD8 Aging Manuscript

  Language:R2001

• dnehar/Temra-IL7R-Senescence

  Pipeline used for the analysis

  Language:Jupyter Notebook1101