Showing 4 open source projects for "stats"

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    Amplicon_Sequencing_Worfklow

    Amplicon_Sequencing_Worfklow

    Analyzing amplicon data from sequences to stats

    This is a collection of scripts and instructions on how to analyzing amplicon sequence data (i.e., 16S, ITS2, & other marker genes). I created this workflow to create a consistent set of methods for analyzing amplicon sequence data, from when you first receive the sequence data to statistical analyses & data visualization. All you need is to have the latest version of R installed, some experience with the command line & shell, and enough memory to run all of the programs. There are also...
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  • 2
    Ionwinze

    Ionwinze

    Spot the differences between samples, groups and classes

    ...How would it be possible to spot an important metabolite or two, from 1000’s that occur in cells and tissues? If those truly relevant metabolites were missed during peak-picking then the following stats, however sophisticated they may be, would fail. And how many peaks are there in a single LCMS run? How can the important metabolites be represented in the top 100 or even 10000 peaks? This project tries to address these issues.
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  • 3
    mitoMaker

    mitoMaker

    mitoMaker - a mitochondria assembly and annotation script

    ...General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).
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  • 4
    ...Our script uses NCBI BLAST run locally and MySQL as the main engines in a new and interisting way. It is designed specifically for Poxvirus genomes, and provides the VACV-COP nomenclature and Cowpox Ortholog groups per each ORF. The BLAST stats are generated when compared to the Proteome you provide. It can be easily adapted for other genomes.
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