Derives genome-based predictions from high-throughput genotyping and large-scale phenotyping data. synbreed contains a comprehensive collection of functions required to fit and cross-validate genomic prediction models. It offers a comprehensive collection of methods required in the analysis of genomic prediction data. synbreed is a valuable tool for the education of young scientists and breeders.
A data integration framework for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available.
Supplies a platform dedicated to the visualization and analyses of data belonging to diverse file formats and experimental protocols. metaseq is a library with the aim of furnishing: (i) a unified interface for ChIP-seq, RNA-seq, RNA immunoprecipitation and sequencing (RIP-seq) experiments, (ii) a mean for converting genomic signal into NumPy arrays as well as (iii) an access to data from commonly used file format such as BAM or GFF.
Provides a novel navigation tool for exploring hierarchical feature data that is coupled with multiple data visualizations including heatmaps, stacked bar charts, and scatter plots. Metaviz is a web browser-based tool for interactive visualization and exploration of metagenomic sequencing data. It also supports common data exploration techniques, including PCA scatter plots to interpret variability in the dataset and alpha diversity boxplots for examining ecological community composition.
Calculates 28 alignment free dissimilarity measures. CAFE allows visualization of pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. It allows the user to study the relationships among genomes and metagenomes. The tool is based on a k-mer alignment-free method and contains 10 conventional measures based on k-mer counts. It also integrates 15 measures based on presence/absence of k-mers.
Serves for metagenomic analysis including the normalization, the differential analysis and multiple visualization. SHAMAN detects the differential abundant genera with the generalized linear model implemented in DESeq2. It allows clinicians and biologists to perform an analysis of quantitative metagenomics data with an interface dedicated to the diagnostic and to the differential analysis. Its process is divided in four steps: count matrix/annotation submission, normalization, schematization and visualization.
Allows to develop workflows in order to perform analyses. BETSY combines a rich data model with an inference engine tuned to reduce the exponential expansion of the search. Users can specify a desired target and the software proposes a solution, and then enters a dialog with the system to refine the proposed pipeline. It is able to run the pipeline obtained and generate the result. The tool can be used as a black box without an understanding of the workflow developed