Pinned Repositories
chromatin_noise_paper
Custom pipeline and scripts for the analysis described in "Systematic Analysis of the Determinants of Gene Expression Noise in Embryonic Stem Cells", Faure et al. 2017
DiMSum
An error model and pipeline for analyzing deep mutational scanning (DMS) data and diagnosing common experimental pathologies
dimsumms
Analysis scripts to reproduce the figures and results from the computational analyses described in the paper Faure and Schmiedel et al. "DiMSum: An error model and pipeline for analyzing deep mutational scanning (DMS) data and diagnosing common experimental pathologies", 2020
DMS2structure
Scripts for "Determining protein structures using deep mutagenesis", Schmiedel & Lehner, Nature Genetics, 2019
doubledeepPCA
scripts for doubledeepPCA for rapid identification of binding interfaces via DMS
Mean-noise-fitness-landscapes
Scripts to reproduce analysis of Schmiedel et al. "Empirical noise-mean fitness landscapes and the evolution of gene expression" bioRxiv, 2018
tempura
R package to fit thermodynamic models to deep mutational scanning data
DiMSum
An error model and pipeline for analyzing deep mutational scanning (DMS) data and diagnosing common experimental pathologies
DMS2structure
Scripts for "Determining protein structures using deep mutagenesis", Schmiedel & Lehner, Nature Genetics, 2019
Mean-noise-fitness-landscapes
Scripts to reproduce analysis of Schmiedel et al. "Empirical noise-mean fitness landscapes and the evolution of gene expression" bioRxiv, 2018
jschmiedel's Repositories
jschmiedel/doubledeepPCA
scripts for doubledeepPCA for rapid identification of binding interfaces via DMS
jschmiedel/chromatin_noise_paper
Custom pipeline and scripts for the analysis described in "Systematic Analysis of the Determinants of Gene Expression Noise in Embryonic Stem Cells", Faure et al. 2017
jschmiedel/DiMSum
An error model and pipeline for analyzing deep mutational scanning (DMS) data and diagnosing common experimental pathologies
jschmiedel/dimsumms
Analysis scripts to reproduce the figures and results from the computational analyses described in the paper Faure and Schmiedel et al. "DiMSum: An error model and pipeline for analyzing deep mutational scanning (DMS) data and diagnosing common experimental pathologies", 2020
jschmiedel/DMS2structure
Scripts for "Determining protein structures using deep mutagenesis", Schmiedel & Lehner, Nature Genetics, 2019
jschmiedel/Mean-noise-fitness-landscapes
Scripts to reproduce analysis of Schmiedel et al. "Empirical noise-mean fitness landscapes and the evolution of gene expression" bioRxiv, 2018
jschmiedel/tempura
R package to fit thermodynamic models to deep mutational scanning data
jschmiedel/microRNA_noise_regulation