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  Analysis of 

ARGOS is a pipeline for extracting intragenomic similarity signals from genomic sequences


ARGOS is a pipeline for extracting three types of one-dimensional signals from a genomic sequence that characterize its repetitiveness. By considering these three signals, one can learn about what parts of a sequence are redundant/copied, how many copies there are and how similar these copies are to each other. This enables insights into genome architecture, genome evolution and generally into the role of repetitive genomic sequences. Please note that an estimated 2/3 of the human genome, for example, are considered repetitive or repeat-derived.

The following three scores are calculated by ARGOS:

Please see here for a poster that describes ARGOS in more detail and was presented at the NGS 2014 conference and here for a technical poster about NextGenScores that was presented at ISMB 2014 conference.

Precalculated tracks

Here you can download pre-calculated ARGOS signals for some model organisms.
You can also directly embed these tracks into the UCSC Genome Browser. Either press the links below or open genome browser and:

  1. Select My Data -> Custom Tracks -> add custom tracks
  2. Enter the respective URIs listed below
  3. press Submit
Use the following URIs to download/access the respective ISS/AMB signals:
Human, chr1 (hg19)
download hg19-CHR1.AMB.wig.bw
open hg19-CHR1.AMB.wig.bw in Genome Browser
download hg19-CHR1.ISS.wig.bw
open hg19-CHR1.ISS.wig.bw in Genome Browser
D. melanogaster, chr2L (FlyBase, r5.26)
download dmel_chr2L.AMB.wig.bw
open dmel_chr2L.AMB.wig.bw in Genome Browser
download dmel_chr2L.ISS.wig.bw
open dmel_chr2L.ISS.wig.bw in Genome Browser
E. coli (K12 MG1655)
download eck12_MG1655_ecoli-chr-GENOME.AMB.wig.bw
open eck12_MG1655_ecoli-chr-GENOME.AMB.wig.bw in Genome Browser
download eck12_MG1655_ecoli-chr-GENOME.ISS.wig.bw
open eck12_MG1655_ecoli-chr-GENOME.ISS.wig.bw in Genome Browser

Getting ARGOS

Please note that ARGOS is work in progress!
ARGOS source code and releases can be downloaded from GitHub. ARGOS uses maven as build tool. For development we recommend the Eclipse IDE for Java developers and the m2e Maven Integration for Eclipse.

The ARGOS jars can be built with bin/build-java.sh <VERSION> (version is, e.g., 0.0.1)

Running ARGOS

ARGOS contains a fully automated python pipeline that basically takes a mFASTA file and some parameters as input and outputs a set of BigWig files (along with some other useful result files) containing the ARGOS scores.

You can call the pipeline using the following command:

				python path/to/argos-pipeline.py [PARAMS]
Calling it w/o parameters will give a basic usage information, calling it with "-h" to get up-to-date usage information:
$ python software/argos-pipeline.py -h
usage: argos-pipeline.py [-h] -g genome [-c [context [context ...]]] -o outdir
                         -t tmpdir [-rl rl] [-step step] [-ctxSize ctxSize]
                         [-dontclean] [-recalcScores recalcScores]
                         [-calcChrom calcChrom] [-gpu]


optional arguments:
  -h, --help            show this help message and exit
  -g genome, --genome genome
                        The mfasta file containing the considered genome
  -c [context [context ...]], --context [context [context ...]]
                        The mfasta files containing the context-genome(s)
  -o outdir, --outdir outdir
                        output directory
  -t tmpdir, --tmpdir tmpdir
                        temp directory
  -rl rl                read length
  -step step            step size
  -ctxSize ctxSize      context size for local signals
  -dontclean            if set to true, the temp files will not be removed
                        (for debugging purposes only!)
  -recalcScores recalcScores
                        force recalculation of mapping scores
  -calcChrom calcChrom  Calculation of per-chromosome ctx scores
  -gpu                  Use GPU for alignment
Please note that this pipeline calls the following external tools: You'll probably have to fix the paths to these tools in the python script (e.g., replace the contents of EXE_NGSTOOLS by "java -jar /path/to/ngs-tools-0.0.1-jar-with-dependencies.jar").