view tools/human_genome_variation/pass.xml @ 1:cdcb0ce84a1b

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<tool id="hgv_pass" name="PASS" version="1.0.0">
  <description>significant transcription factor binding sites from ChIP data</description>

  <command interpreter="bash">
    pass_wrapper.sh "$input" "$min_window" "$max_window" "$false_num" "$output"
  </command>

  <inputs>
    <param format="gff" name="input" type="data" label="Dataset"/>
    <param name="min_window" label="Smallest window size (by # of probes)" type="integer" value="2" />
    <param name="max_window" label="Largest window size (by # of probes)" type="integer" value="6" />
    <param name="false_num" label="Expected total number of false positive intervals to be called" type="float" value="5.0" help="N.B.: this is a &lt;em&gt;count&lt;/em&gt;, not a rate." />
  </inputs>

  <outputs>
    <data format="tabular" name="output" />
  </outputs>

  <requirements>
    <requirement type="package">pass</requirement>
    <requirement type="binary">sed</requirement>
  </requirements>

  <!-- we need to be able to set the seed for the random number generator
  <tests>
    <test>
      <param name="input" ftype="gff" value="pass_input.gff"/>
      <param name="min_window" value="2"/>
      <param name="max_window" value="6"/>
      <param name="false_num" value="5"/>
      <output name="output" file="pass_output.tab"/>
    </test>
  </tests>
  -->

  <help>
**Dataset formats**

The input is in GFF_ format, and the output is tabular_.
(`Dataset missing?`_)

.. _GFF: ./static/formatHelp.html#gff
.. _tabular: ./static/formatHelp.html#tab
.. _Dataset missing?: ./static/formatHelp.html

-----

**What it does**

PASS (Poisson Approximation for Statistical Significance) detects
significant transcription factor binding sites in the genome from
ChIP data.  This is probably the only peak-calling method that
accurately controls the false-positive rate and FDR in ChIP data,
which is important given the huge discrepancy in results obtained
from different peak-calling algorithms.  At the same time, this
method achieves a similar or better power than previous methods.

<!-- we don't have wrapper support for the "prior" file yet
Another unique feature of this method is that it allows varying
thresholds to be used for peak calling at different genomic
locations.  For example, if a position lies in an open chromatin
region, is depleted of nucleosome positioning, or a co-binding
protein has been detected within the neighborhood, then the position
is more likely to be bound by the target protein of interest, and
hence a lower threshold will be used to call significant peaks.
As a result, weak but real binding sites can be detected.
-->

-----

**Hints**

- ChIP-Seq data:

  If the data is from ChIP-Seq, you need to convert the ChIP-Seq values
  into z-scores before using this program.  It is also recommended that
  you group read counts within a neighborhood together, e.g. in tiled
  windows of 30bp.  In this way, the ChIP-Seq data will resemble
  ChIP-chip data in format.

- Choosing window size options:

  The window size is related to the probe tiling density.  For example,
  if the probes are tiled at every 100bp, then setting the smallest
  window = 2 and largest window = 6 is appropriate, because the DNA
  fragment size is around 300-500bp.

-----

**Example**

- input file::

    chr7  Nimblegen  ID  40307603  40307652  1.668944     .  .  .
    chr7  Nimblegen  ID  40307703  40307752  0.8041307    .  .  .
    chr7  Nimblegen  ID  40307808  40307865  -1.089931    .  .  .
    chr7  Nimblegen  ID  40307920  40307969  1.055044     .  .  .
    chr7  Nimblegen  ID  40308005  40308068  2.447853     .  .  .
    chr7  Nimblegen  ID  40308125  40308174  0.1638694    .  .  .
    chr7  Nimblegen  ID  40308223  40308275  -0.04796628  .  .  .
    chr7  Nimblegen  ID  40308318  40308367  0.9335709    .  .  .
    chr7  Nimblegen  ID  40308526  40308584  0.5143972    .  .  .
    chr7  Nimblegen  ID  40308611  40308660  -1.089931    .  .  .
    etc.

  In GFF, a value of dot '.' is used to mean "not applicable".

- output file::

    ID  Chr   Start     End       WinSz  PeakValue  # of FPs  FDR
    1   chr7  40310931  40311266  4      1.663446   0.248817  0.248817

-----

**References**

Zhang Y. (2008)
Poisson approximation for significance in genome-wide ChIP-chip tiling arrays.
Bioinformatics. 24(24):2825-31. Epub 2008 Oct 25.

Chen KB, Zhang Y. (2010)
A varying threshold method for ChIP peak calling using multiple sources of information.
Submitted.

  </help>
</tool>