Methylation data tools. Arrow based tables for efficiently storing and processing Bismark BAMs. Module for producing pile-up images of regions for CNNs.

Images for CNN

2D pileups, as binary arrays with values between 0 & 1 representing different sequence features such as methylation state, mapping quality and nucleotide sequence.

Paired-end BAMs should be sorted by query name (preferably) or coordinate (may take more memory). Unsorted BAMs will probably work but use a lot of memory.

Generation

After installation use jtm-generate-images run --help for arguments. Available layers (that can then be passed to the --layer option) can be printed using jtm-generate-images layers. run produces gzipped TAR files that contain the binary array and a metadata JSON file, specifying the shape of the array and other things.

jtm-generate-images invokes the script generate_images.py.

Loading arrays

import jtmethtools as jtm
fn = 'image.region_name.layer.tar.gz'
array, metadata = jtm.images.read_array(fn)

plot an array

plt.imshow(array, interpolation='nearest', cmap='gray')