# The Wiggle pipeline

The wiggle pipeline produces something equivalent to a wiggle plot commonly seen when viewing NGS data in generic genome browsing systems. This provides a simple view of the quantitated density of reads along either a specific region, or over the whole genome, giving a more quantitative way of looking at your raw data than looking at the raw reads directly, but with no bias for specific regions.

The wiggle view isn't particularly useful for analysing your data, but is mostly used as a better way to take an initial view of how your data is distributed over your genome.

## Options

The options you can set for this pipeline are:

1. Which area you want to look at. You can choose to cover either the whole genome, the current chromosome or the currently visible region. Looking at smaller regions will allow you to place your probes more densely, since it is the total number of probes which tends to be limiting. When you change this selection SeqMonk will automatically suggest sensible values for the width of your probes, but you are free to igore these and set your own size.
2. The width and step size for your probes. These will be set automatically based on the size of the region you're analysing (the program aims to make 10 million probes and adjusts the size of each probe to try to match this figure). By default the step size and probe width will be the same so probes don't overlap, but you can alter this value to whatever you like. You should be aware that reducing the suggested step size could generate very large numbers of probes which could take a long time and a lot of resources to calculate.
3. Whether the results should be log2 transformed. The default is to quantitate on a linear scale to emphasize any differences, but you can choose to use a log scale if this makes more sense for your data. If your data is on a linear scale you will probably need to adjust the automatically calibrated y-scale to allow you to see the high outliers.
4. Whether you want to adjust your counts based on the total number of reads in your datasets. Setting this option will allow for a more direct comparison of your samples