comparison small_rna_maps.xml @ 23:3ca8113cc758 draft

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_rna_maps commit 15cc0c091844f9b87dc2ec2abd773b4aa26e2a67

22:29f03c13c7a2

<tool id="small_rna_maps" name="small_rna_maps" version="2.11.0">
  <description></description>
  <requirements>
        <requirement type="package" version="1.11.2=py27_0">numpy</requirement>
        <requirement type="package" version="0.11.2.1=py27_0">pysam</requirement>
        <requirement type="package" version="1.3.2=r3.3.2_0">r-optparse</requirement>

    </tests>
<help>

**What it does**

Plots mapping statistics of an alignment along the reference chromosomes :

 - counts
 - mean sizes
 - median sizes
 - coverage depth

Or in all possible pairwise combinations:

.. image:: two_plot.png

For comparison purposes, values from bam alignment files can be normalized by a size factor
before plotting.

**Inputs**

bam alignment files that must be

  - single-read
  - sorted
  - mapped to the same reference

To plot 2 alignment files in the same PDF output the 'single dataset' method should be used.

.. class:: warningmark

If the 'multiple dataset' method is used the normalization factor will be applied to every file selected in the input list.
Additionally each file in the selected list will be plotted in a separate PDF file.

**Output**

A pdf file generated by the R package lattice and one or two dataframes used to plot the data.

23:3ca8113cc758

<tool id="small_rna_maps" name="small_rna_maps" version="2.11.1">
  <description></description>
  <requirements>
        <requirement type="package" version="1.11.2=py27_0">numpy</requirement>
        <requirement type="package" version="0.11.2.1=py27_0">pysam</requirement>
        <requirement type="package" version="1.3.2=r3.3.2_0">r-optparse</requirement>

    </tests>
<help>

**What it does**

Plots mapping statistics of read alignments along reference chromosomes or genes or arbitrary regions :

 - counts
 - mean sizes
 - median sizes
 - coverage depth

Or in all possible pairwise combinations:

.. image:: two_plot.png

For comparison purposes, values from bam alignment files can be normalized by a size factor
before plotting (Normalisation field)

*Cluster mode*

Cluster of read alignments are aggregated along regions of *variable* lengths. The Clustering
algorithm works as follows:

A read is clustered with the following read on the genomic reference if the two reads are
separated by at maximum the clustering distance (set in nucleotides). If clustered, the step is
repeated with the following read until clustering fails. A new cluster is then searched.

For clustering procedure, one has the possibility to consider the polarity of reads (only forward
reads or reverse reads can be clustered separately), or to ignore this polarity.

Cluster reads are plotted as for single reads, their coordinate being the median of extrem coordinates of the cluster.

In addition, cluster are reported in a bed file, where clusters can be filtered out upon various parameters,
cluster size, cluster read number or cluster read density (number of reads divided by the length of the cluster).

**Inputs**

bam alignment files that must be

  - single-read
  - sorted
  - mapped to the same reference

.. class:: warningmark

This tools follows a "map-reduce" procedure: multiple inputs, that can be arranged as a data collection,
are visualised side by side in a single pdf file.
 


**Output**

A pdf file generated by the R package lattice and one or two dataframes used to plot the data.