Tag Results

galaxy_101 (2)

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  This is a Galaxy pipeline written using the Galaxy 101 tutorial (https://main.g2.bx.psu.edu/galaxy101). The pipeline involves retrieving genome and SNP data from UCSC for a particular chromosome. These data are integrated in order to find exons with the highest number of SNPs.

Created: 2012-06-13 | Last updated: 2012-06-14

Credits: Peter Li

Perform QC on FastQ data (1)

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 This Galaxy pipeline performs quality control analyses on FastQ data. A report is generated which provides various measures of the quality of the sequence reads.

Created: 2012-06-14 | Last updated: 2012-06-14

Advanced FastQ manipulation (1)

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 This Galaxy workflow performs advanced FastQ manipulation as demonstrated by the screencast at http://screencast.g2.bx.psu.edu/quickie_14_fastq_adv/flow.html. Given a FastQ set of data, it will be transformed using the tools, Groomer, Filter FastQ, FastQ Trimmer, Manipulate FastQ before it is finally converted into FASTA format.

Created: 2012-06-14 | Last updated: 2012-06-14

Gene enhancer region analysis (1)

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 This Galaxy pipeline searches for transciption factor binding sites which are conserved through to Fugu. It then finds genes associated with these enhancer binding sites. See http://screencast.g2.bx.psu.edu/MAF_manipulation for the screencast that describes how this workflow is developed.

Created: 2012-06-14 | Last updated: 2012-07-06

Calculate ellipses that describe a galaxy ... (2)

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This workflow calculates the ellipses that better match a galaxy by doing two iterations. In the first one the center and the outer ellipse are aproximated because there might be bars that affect to the inner ellipses. In the second one, files with the ellipse data are built. It creates ellipse scripts using data from a votable, it runs ellipse, its results are added to the votable, it creates new scripts for ellipse using the previous results, it runs ellipse a second time and it finally in...

Created: 2012-08-07 | Last updated: 2012-09-11

Credits: Julian Garrido

Attributions: Create configuration files from a template and a votable Run scripts from a column in a votable Create votable from ellipse results Detect ellipse failures and get votable without ellipse failures

Create votable from different galfit param... (2)

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The workflow creates a votable from the results provided by galfit. It returns this table and an aditional table that is joined to the input table. It requires a votable that contains a column with the file name resulting from running galfit and such files must be accesible from taverna. It uses astrotaverna plugin (http://wf4ever.github.com/astrotaverna/) and it has a dependency on stil library (http://www.star.bris.ac.uk/~mbt/stil/). The galfit files may come from adjusting 'disk, bulb, ba...

Created: 2012-08-21 | Last updated: 2012-09-07

Credits: Julian Garrido

Add columns to a votable resulting from ex... (1)

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Addcolumns that are needed to run galfit and ellipse. it requires columns coming from sextractor and the astrotaverna plugin.

Created: 2012-08-30

Credits: Julian Garrido

Build plots from galfit and ellipse results (2)

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Build plots from galfit and ellipse results (http://www.myexperiment.org/workflows/3068.html, http://www.myexperiment.org/workflows/3052.html).

Created: 2012-08-30 | Last updated: 2012-09-07

Credits: Julian Garrido

Detect ellipse failures and get votable wi... (1)

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It detects if ellipse has failed by checking if the resulting data file exists. It adds a column (validellipse) that contains 1 if ellipse didn't fail and 0 if ellipse failed. It returns a votable that contains all the data with the new column and a votable that contains only the rows where ellipse didn't failed. It uses astrotaverna plugin (http://wf4ever.github.com/astrotaverna/).

Created: 2012-09-07

Credits: Julian Garrido

Detrprok (4)

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In the case study of stranded and prokaryotic RNAseq data, the Det'Rprok workflow detects candidates of 3 kinds of non coding RNA: 5'UTRs, antisense RNAs, and small RNAs.Inputs: i) an mapping file (bam format) containing one valid alignment by read, ii) a feature file (gff format) annotating the genomic sequences used for the mapping. Dependencies (from the Galaxy toolshed): "s_mart", "detrprok_scripts"

Created: 2013-05-20 | Last updated: 2015-11-03

Clustered heatmap of signals around the TSSs (1)

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Galaxy workflow based on deepTools which creates a clustered heatmap of signals around the TSS. One bigwig file is needed as input with the signal and an annotation file with your TSS regions. The output will be a heatmap. You can create such a bigwig file with the bamCorrelate toolFor more information please see the deepTools wiki. This workflow is also available via the Galaxy Tool Shed.

Created: 2014-04-03 | Last updated: 2014-04-03

Credits: Björn Grüning

Heatmap of read coverages (1)

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Created: 2014-04-03

Credits: Björn Grüning

Heatmap of read coverages (single BAM file) (1)

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Created: 2014-04-03

Credits: Björn Grüning

Compute and correct GC bias in NGS data (1)

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Galaxy workflow based on deepTools which will compute and correct GC bias in your NGS data. For more information please see the deepTools wiki. This workflow is also available via the Galaxy Tool Shed.

Created: 2014-04-03

Credits: Björn Grüning

Galaxy workflow for the identification of ... (1)

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This approach screens three proteins against a given genome sequence, leading to a genome position were all three genes are located nearby. As usual in Galaxy workflows every parameter, including the proximity distance, can be changed and additional steps can be easily added. For example additional filtering to refine the initial BLAST hits, or inclusion of a third query sequence.https://github.com/bgruening/galaxytools/tree/master/workflows/ncbi_blast_plus/find_three_genes_located_nearby

Created: 2015-03-17

Credits: Björn Grüning

AmrPlusPlus Paired Workflow (9)

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Created: 2016-08-05 | Last updated: 2016-11-18

Credits: Chris

AmrPlusPlus Single Workflow (2)

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Created: 2016-08-12 | Last updated: 2017-01-05

Credits: Chris