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Jie Zhu's Projects

.tmux icon .tmux

🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️

16s-dada2 icon 16s-dada2

Snakemake pipeline for amplicon sequencing using dada2

2019-ncov-japan icon 2019-ncov-japan

🦠 Interactive dashboard for real-time recording of COVID-19 outbreak in Japan

abricate icon abricate

:mag_right: :pill: Mass screening of contigs for antimicrobial and virulence genes

ameta icon ameta

Ancient microbiome snakemake workflow

ancientmetagenomedir icon ancientmetagenomedir

Repository containing lists of all published ancient metagenomic (and related) samples and libraries

anvio icon anvio

An analysis and visualization platform for 'omics data

arcashla icon arcashla

Fast and accurate in silico inference of HLA genotypes from RNA-seq

args_oap icon args_oap

ARGs-OAP: Online Analysis Pipeline for Antibiotic Resistance Genes Detection from Metagenomic Data Using an Integrated Structured ARG Database

armor icon armor

Light-weight Snakemake workflow for preprocessing and statistical analysis of RNA-seq data

asap icon asap

A scalable bacterial genome assembly, annotation and analysis pipeline

atlas icon atlas

ATLAS - Three commands to start analysing your metagenome data

autocd icon autocd

Automated synthetic microbial Community Design

aviary icon aviary

A snakemake pipeline for binning metagenomic assemblies

awesome-vdj icon awesome-vdj

Tools and databases for analyzing HLA and VDJ genes.

bacassembly icon bacassembly

hybrid assembly and polish using short and long reads

bactopia icon bactopia

A flexible pipeline for complete analysis of bacterial genomes

bakta icon bakta

Rapid & standardized annotation of bacterial genomes, MAGs & plasmids

bandageng icon bandageng

a Bioinformatics Application for Navigating De novo Assembly Graphs Easily

benchmark_microbiome_transformations icon benchmark_microbiome_transformations

Code to reproduce the analyses from the paper "Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases"

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