comparison transit_tn5gaps.xml @ 1:c68753eedf72 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/transit/ commit bd061799ebd49ada1a666d0815720c18291728da"

0:e4f44f327cf1

<?xml version="1.0"?>
<tool id="transit_tn5gaps" name="Tn5Gaps" version="@VERSION@+galaxy1">
    <description>- determine essential genes</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />

         -m $smallest
        ]]>
    </command>
    <inputs>
        <expand macro="standard_inputs">
            <param name="smallest" argument="-m" type="integer" value="1" label="Smallest read-count to consider" />
        </expand>
    </inputs>
    <outputs>
        <expand macro="outputs" />

-------------------

Optional Arguments:
       -m <integer>    :=  Smallest read-count to consider. Default: -m 1
       -r <string>     :=  How to handle replicates. Sum or Mean. Default: -r Sum
       --iN <float>     :=  Ignore TAs occuring at given fraction of the N terminus. Default: -iN 0.0
       --iC <float>     :=  Ignore TAs occuring at given fraction of the C terminus. Default: -iC 0.0
       -n <string>      := Determines which normalization method to use. Default -n TTR

- Minimum Read: The minimum read count that is considered a true read. Because the Gumbel method depends on determining gaps of TA sites lacking insertions, it may be susceptible to spurious reads (e.g. errors). The default value of 1 will consider all reads as true reads. A value of 2, for example, will ignore read counts of 1.
- Replicates: Determines how to deal with replicates by averaging the read-counts or summing read counts across datasets. This should not have an affect for the Gumbel method, aside from potentially affecting spurious reads.
- Normalisation :
    - TTR (Default) : Trimmed Total Reads (TTR), normalized by the total read-counts (like totreads), but trims top and bottom 5% of read-counts. This is the recommended normalization method for most cases as it has the beneffit of normalizing for difference in saturation in the context of resampling.

1:c68753eedf72

<?xml version="1.0"?>
<tool id="transit_tn5gaps" name="Tn5Gaps" version="@VERSION@+galaxy2">
    <description>- determine essential genes</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />

         -m $smallest
        ]]>
    </command>
    <inputs>
        <expand macro="standard_inputs">
            <expand macro="handle_replicates" />
            <param name="smallest" argument="-m" type="integer" value="1" label="Smallest read-count to consider" />
        </expand>
    </inputs>
    <outputs>
        <expand macro="outputs" />

-------------------

Optional Arguments:
       -m <integer>    :=  Smallest read-count to consider. Default: -m 1
       -r <string>     :=  How to handle replicates. Sum or Mean. Default: -r Mean
       --iN <float>     :=  Ignore TAs occuring at given fraction of the N terminus. Default: -iN 0.0
       --iC <float>     :=  Ignore TAs occuring at given fraction of the C terminus. Default: -iC 0.0
       -n <string>      := Determines which normalization method to use. Default -n TTR


- Minimum Read: The minimum read count that is considered a true read. Because the Gumbel method depends on determining gaps of TA sites lacking insertions, it may be susceptible to spurious reads (e.g. errors). The default value of 1 will consider all reads as true reads. A value of 2, for example, will ignore read counts of 1.
- Replicates: Determines how to deal with replicates by averaging the read-counts or summing read counts across datasets. This should not have an affect for the Gumbel method, aside from potentially affecting spurious reads.
- Normalisation :
    - TTR (Default) : Trimmed Total Reads (TTR), normalized by the total read-counts (like totreads), but trims top and bottom 5% of read-counts. This is the recommended normalization method for most cases as it has the beneffit of normalizing for difference in saturation in the context of resampling.