report descriptions for homer annotatePeaks and phantompeakqualtools

workflow/report/plot_annotatepeaks_homer.rst

+**`Homer annotatePeaks <http://homer.ucsd.edu/homer/ngs/annotation.html>`_ ** is used to annotate the peaks relative
+to known genomic features. The plots of this analysis show for all samples and their associated controls peak location
+relative to annotation, percentage of unique genes to closest peak an peak distribution relative to TSS
+(Transcription Start Site).

workflow/report/plot_phantompeak_phantompeakqualtools.rst

- 
+ **`Phantompeakqualtools plot <https://code.google.com/archive/p/phantompeakqualtools/>`_** shows strand-shift versus
+cross-correlation and computes informative enrichment and quality measures for ChIP-seq data. It also calculates the
+relative (RSC) and the normalized strand cross-correlation coefficient (NSC). Datasets with NSC values much less than
+1.1 tend to have low signal to noise or few peaks. This may indicate poor quality or only few binding sites. RSC values
+significantly lower than 1 (< 0.8) tend to have low signal to noise. The low scores can be due to several factors and
+are often due to failed and poor quality ChIP or low read sequence quality. In section "ChIP-seq processing pipeline"
+of MultiQC report are additional plots across all samples for RSC, NSC and strand-shift cross-correlation.
+ For more information about Phantompeakqualtools please
+see `documentation <https://github.com/kundajelab/phantompeakqualtools/blob/master/README.md>`_. For more information
+about interpretation see published `article <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431496/>`_.

workflow/rules/post-analysis.smk

@@ -185,7 +185,7 @@ rule plot_heatmap:
 rule phantompeakqualtools:
     input:
         "results/filtered/{sample}.sorted.bam"
-    output:  #ToDo: add description to report caption
+    output:
         res_phantom="results/phantompeakqualtools/{sample}.phantompeak.spp.out",
         r_data="results/phantompeakqualtools/{sample}.phantompeak.Rdata",
         plot=report(