Read Builder

A somewhat generic system for classifying the channel state throughout the course of an experiment.

Here, a read is a contiguous run of events/raw data points that correspond to an identifiable channel state.

We follow the same three-step process used in previous implementations, but allow for some useful additions.

1. Determine read boundaries: Calculates start and end coordinates of reads, and outputs reads as raw or event data. Naively, neighbouring reads are ultimately expected to be assigned different classes.

2. Calculate metrics on reads: Takes event (or raw) data provided by step 1. and calculates summary statistics (of arbitrary complexity). May optionally take exogenous data concerning the state of a channel, e.g. saturation status.

3. Classify reads: Takes the matrix of metrics for a read (and possibly the metrics of surrounding reads) to output an additional metric: the classification.

The smart cookie notices that this system is rather backwards: one would hope to label read boundaries by running a classifier over a channel and outputting boundaries where there is a state change. The above does not exclude this; step 1. could be arbitrarily complex. The framework requires only that it output read data (and optionally key-value pairs of meta data).

The key differences between the current framework and previous incarnations are:

• Clear separation of the three steps.
• The ability to calculate classes based on metrics of surrounding reads.
• Defined interface to each step such that the methodology used in each can be changed depending on the application.
• Low memory use: reads are processed individually rather than storing all data for a channel in memory.
• Multiprocessing across channels.

Installation

Panga installs into a virtual environment. Installation should should be as simple as running
Make install

On Ubuntu, you will need to install the virtualenv and python-dev packages. sudo apt-get install python-virtualenv python-dev

Running read_builder

Panga read_builder is installed into a virtual environment. To run it first activate your environment source panga_directory/venv/bin/activate

To analyse Minknow reads use: read_builder --fast5 path_to_bulk_hdf --config $(panga_config_dir)/standard_minknow_classes.yml --outpath read_builder --summary_file read_summary.txt

Example configs for more advanced analyses such as redetection of read boundaries, read metrics and classifications can be found in the panga config directory: ls $(panga_config_dir)