Deep mutational scanning data analysis software tools
Mutagenesis provides insight into proteins, but only recently have assays that couple genotype to phenotype been used to assess the activities of as many as 1 million mutant versions of a protein in a single experiment. This approach-'deep mutational scanning'-yields large-scale data sets that can reveal intrinsic protein properties, protein behavior within cells and the consequences of human genetic variation. Deep mutational scanning is transforming the study of proteins, but many challenges must be tackled for it to fulfill its promise.
Consists of a statistical framework for analyzing deep mutational scanning data. Enrich2 aims to improve the access to deep mutational scanning for labs without data analysis experience. The software includes scoring methods applicable to deep mutational scans with any number of time points. It facilitates removal of noisy variants and detection of variants of small effect and enables statistically rigorous comparisons between variants.
Analyzes deep mutational scanning data. Enrich incorporates scoring methods applicable to deep mutational scans with any number of time points. It predicts variant scores and standard errors that mirror both sampling error and consistency between replicates. This software measures an enrichment ration to estimate fitness via the frequency of each variant before and after selection. It offers an alignment-free mode and an implementation of the Needleman-Wunsch global alignment algorithm to call insertion and deletion events.
A software package to infer the impacts of mutations from deep mutational scanning data using a likelihood-based treatment of the mutation counts. Using dms_tools, one can infer the preference of each site for each amino acid given a single selection pressure, or assess the extent to which these preferences change under different selection pressures. The preferences and their changes can be intuitively visualized with sequence-logo-style plots created using an extension to Weblogo.
Provides utilities for downstream analysis such as identification of relative selection pressure, molecular constraints and visualizations of the data. dms2dfe is a tunable, open-source workflow that integrates state-of-the-art methods of genomics for analysis of deep mutational scanning (DMS) data. It implements noise reduction utilizing both sequencing depth and empirical Bayes shrinkage. This package also supports concatamer based approach as well as multiplexing strategy using barcoded amplicons.
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