Christian Roth (croth1)

croth1

Geek Repo

Company:QuantCo

Location:Berlin, Germany

Twitter:@croth44

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Christian Roth's starred repositories

wtfpython

What the f*ck Python? 😱

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msgpack-c

MessagePack implementation for C and C++ / msgpack.org[C/C++]

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common-workflow-language

Repository for the CWL standards. Use https://cwl.discourse.group/ for support 😊

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cwltool

Common Workflow Language reference implementation

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docker

Official Docker project for Matomo Analytics

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nb_conda_kernels

Package for managing conda environment-based kernels inside of Jupyter

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sim_iCLIP

Simulation framework for iCLIP/eCLIP-seq data

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PureCLIP

Capturing protein-RNA interaction footprints from single-nucleotide CLIP-seq data

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hub

A command-line tool that makes git easier to use with GitHub.

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jedi-vim

Using the jedi autocompletion library for VIM.

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docker-alpine

Alpine Linux Docker image. Win at minimalism!

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django-dbbackup

Management commands to help backup and restore your project database and media files

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web

The web front end for Overleaf, a web-based collaborative LaTeX editor

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BaMM_webserver

Webserver for motif discovery with higher-order Bayesian Markov Models (BaMMs)

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notebook

Jupyter Interactive Notebook

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scipy

SciPy library main repository

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merlot

Reconstruct the lineage topology of a scRNA-seq differentiation dataset.

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prosstt

PRObabilistic Simulations of ScRNA-seq Tree-like Topologies

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omniCLIP

omniCLIP is a CLIP-Seq peak caller

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pyfaidx

Efficient pythonic random access to fasta subsequences

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bedtools2

bedtools - the swiss army knife for genome arithmetic

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PARpipe

Complete analysis pipeline for PAR-CLIP data

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BaMMmotif2

Bayesian Markov Model motif discovery tool version 2 - An expectation maximization algorithm for the de novo discovery of enriched motifs as modelled by higher-order Markov models.

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genomepy

genes and genomes at your fingertips

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sphinx

The Sphinx documentation generator

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hieroglyph

Generate HTML presentations from plain text sources with all the power of Sphinx.

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b-lore

Bayesian multiple logistic regression for GWAS meta-analysis

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