xiRT is a python package for multi-dimensional RT prediction for linear and cross-linked peptides.
xiRT is a deep learning application and uses a Siamese network to encode crosslinked peptides. xiRT can predict continuous and discrete retention times (e.g. from reversed phase or fractionation experiments).
xiRT requires a running python installation, please follow the installation guide to get xiRT running. To visualize the neural network pydot and graphviz are also needed.
A GPU is not necessary to use xiRT. It speeds things up but xiRT can run on any desktop computer. Make sure to specify the correct layer in the xirt_params file (e.g. GRU instead of CudNNGRU).
Depends heavily on the settings (e.g. cross-validation folds, epochs, number input PSMs). For the example data (3-fold crossvalidation, 17k PSMs, 25 epochs) the analysis finishes within 10 minutes on a desktop pc.
Please create an GitHub issue if we can assist you with your analysis or if anything is unclear.
xiRT is agnostic to the type of chromatography and supports to learn 1, 2,3 ..., n chromatography dimensions at the same time. Continuous (e.g. reversed phase) and discrete (fractionation) retention time measurements are supported.
When using xirt over the command line, make sure to allways use the relative or absolute path to the input files.
The current matplotlib version (3.3) seems to have a bug. Please install matplitlib 3.2 (pip install matplotlib==3.2).