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Description: Format RST documentation into input for rst2man
Author: Afif Elghraoui <afif@ghraoui.name>
Forwarded: not-needed
Last-Update: 2015-12-09
Index: kineticstools/doc/manual.rst
===================================================================
--- kineticstools.orig/doc/manual.rst
+++ kineticstools/doc/manual.rst
@@ -1,9 +1,16 @@
+==========
+ipdSummary
+==========
+
+------------------------------------------------------
+Detect DNA base-modifications from kinetic signatures.
+------------------------------------------------------
+:Date: December 2015
+:Manual section: 1
-
-========
-Overview
-========
+DESCRIPTION
+===========
kineticsTool loads IPDs observed at each position in the genome, and compares those IPDs to value expected for unmodified DNA, and outputs the result of this statistical test.
The expected IPD value for unmodified DNA can come from either an *in-silico control* or an *amplified control*. The in silico control is trained by PacBio and shipped with the package. It predicts predicts the IPD using the local sequence context around the current position.
@@ -27,8 +34,11 @@ kineticsTools also has a *Modification I
* Different modifications occuring on the same base can be distinguished (for example m5C and m4C)
* The signal from one modification is combined into one statistic, improving sensitivity, removing extra peaks, and correctly centering the call
+OPTIONS
+=======
+
+Please call this program with **--help** to see the available options.
-=========
Algorithm
=========
@@ -55,7 +65,6 @@ Statistical Testing
We test the hypothesis that IPDs observed at a particular locus in the sample have a longer means than IPDs observed at the same locus in unmodified DNA. If we have generated a Whole Genome Amplified dataset, which removes DNA modifications, we use a case-control, two-sample t-test. This tool also provides a pre-calibrated 'synthetic control' model which predicts the unmodified IPD, given a 12 base sequence context. In the synthetic control case we use a one-sample t-test, with an adjustment to account for error in the synthetic control model.
-=============
Example Usage
=============
@@ -68,7 +77,6 @@ With dataset input, methyl fraction calc
ipdSummary mapped.alignmentset.xml --reference ref.fasta --identify m6A,m4C --methylFraction --gff basemods.gff --csv kinetics.csv
-======
Inputs
======
@@ -84,7 +92,6 @@ Reference Sequence
The tool requires the reference sequence used to perform alignments. This can
be either a FASTA file or a ReferenceSet XML.
-=======
Outputs
=======
@@ -179,3 +186,8 @@ coverage mean of case and
controlCoverage count of valid control IPDs at this position (see Filtering section for details)
caseCoverage count of valid case IPDs at this position (see Filtering section for details)
================ ===========
+
+SEE ALSO
+========
+
+**summarizeModifications**\ (1)
|
