EaSeq

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Application data

Created by Lerdrup M, Johansen JV, Agrawal-Singh S, Hansen KH
Biological application domain(s) ChIP-Seq
Principal bioinformatics method(s) Analysis, Biological interpretation, Clustering, Correlation, Enrichment, Filtering, Format conversion, Genome visualisation, Genomic region matching, Global test, Integrated solution, Peak calling, Visualisation Quality assessement, Read summarisation, Regression analysis, Viewer, Visualisation, and more...
Technology Any HTS
Created at University of Copenhagen
Maintained? Yes
Input format(s) Bed, Bam, BedGraph, Wig, Aln, CSV, Compressed/uncompressed, Customizable, Delimited Text
Output format(s) Tif, Bed, BedGraph, Wig, Aln, Compressed/uncompressed, Delimited Text, .eas (Custom Session file format)
Software version 1.02
Software features Interactive, User-friendly, GUI, WYSIWYG, ChIPseq analysis, Data Visualisation, Data analysis, Genome Viewer, Integrated solution, Memory efficient, Multicore, Integrated tutorials, Automatic documentation, Integrated chat forum
Interface type(s) Desktop GUI
Resource type(s) Tool"Tool" is not in the list (Command-line tool, Web application, Desktop application, Script, Suite, Workbench, Database portal, Workflow, Plug-in, Library, ...) of allowed values for the "Resource type" property., Platform"Platform" is not in the list (Command-line tool, Web application, Desktop application, Script, Suite, Workbench, Database portal, Workflow, Plug-in, Library, ...) of allowed values for the "Resource type" property.
Software libraries NET framework 4 (Windows)
Licence Freeware, Custom Licence
Operating system(s) Windows 7 or Higher
Contact: mads.lerdrup@bric.ku.dk

Summary: EaSeq is developed for user-friendly exploration, visualization and analysis of genome-wide single-read sequencing data (mainly ChIP-seq). Both individual genomic loci and populations of loci can be visualized e.g. as plots of average signals, scatter diagrams, or clustered heatmaps. The underlying loci can then be inspected just by selecting them in the plots - or they can be 'gated out' for further analysis. EaSeq also integrates more than 20 tools for analysis, including peak-finding, quantitation, normalization, clustering, distance analysis, randomization, scoring, and normalization. Finally, it automatically generates legends and descriptions of the handling and can store plots together with underlying data and these descriptions as a single compact session file. 200px|right

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Description

Links


References

  1. . 2016. Nat Struct Mol Biol


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