Plots for WGA P values rgManQQ.py '$i' "$name" '$out_html' '$out_html.files_path' '$chrom_col' '$offset_col' '$pval_col' '$grey'

.. class:: infomark **Syntax** - **Tabular Data** is a tab delimited header file with chromosome, offset and p values to be plotted - **Chromosome Column** is the column in that data containing the chromosome as an integer - **Offset Column** contains the offset within the chromosome - **P Value Column** contains the (untransformed) p values at that locus - choose multiple columns if needed NOTE - plotting millions of p values may take tens of minutes depending on how busy the server is - be patient please. ----- .. class:: infomark **Summary** This tool will create a qq plot and a Manhattan plot for one or more GWA P value columns from a tabular dataset. For Manhattan plots, the data must include the chromosome (eg use 23,24,25 for x,y,mt...) and offset. Many analysis files contain the required fields but even without chromosome and offset, a qq plot can be created. ----- .. class:: infomark **Explanation** A "Manhattan" plot shows -log10 p values ordered by offset and by chromosome. Regions with interestingly improbable p values are above the red line which is drawn at the Bonferroni FWER control level (0.05/n where n is the number of tests - this is highly conservative for correlated SNPs typical of GWA) .. image:: ../static/images/Armitagep_manhattan.png A quantile-quantile (QQ) plot is a good way to see systematic departures from the null expectation of uniform p-values from a genomic analysis. If the QQ plot shows departure from the null (ie a uniform 0-1 distribution), you hope that this will be in the very smallest p-values suggesting that there might be some interesting results to look at. A log scale will help emphasise departures from the null at low p values more clear .. image:: ../static/images/Armitagep_qqplot.png ----- .. class:: infomark **Attribution** This is a Galaxy tool written by Ross Lazarus. It relies on ggplot2, an R package from hadley wickham and some R code for manhattan and qq plots using ggplot2, borrowed from Stephen Turner found at http://GettingGeneticsDone.blogspot.com/ copyright Ross Lazarus 2010 Licensed under the terms of the LGPL as documented http://www.gnu.org/licenses/lgpl.html but is about as useful as a chocolate teapot without R and Galaxy which all have a twisty maze of little licenses, all different. I'm no lawyer, but it looks like at least LGPL if you create derived works from this code. Good luck.