Hi All, Thank you again for participating in the challenge. We have been actively working on setting up cloud environments that can handle the compute and memory requirements for the models. Its been more challenging logistically than anticipated. But we want to move ahead with getting the write ups, models and code so that we can validate everything. Details instructions for submitting write ups, models and code are on the wiki at https://www.synapse.org/#!Synapse:syn17083203/wiki/600184 . Please follow the instructions EXACTLY as specified in the wiki. A summary for what we need from all of you: (1) An editable write-up (Google doc, word, overleaf, NOT PDF) fully describing your approach as you would to someone who wanted to reproduce your method from scratch. Also, the names and affiliations of everyone involved in the group. (2) The trained models that the imputations you submitted are from. (3) Code that can take this trained model and make the imputations that you submitted. The output of this code should be bigwigs for every test set track. (4) Your code for handling data, starting at bigwig files, and training a model. This does not necessarily have to produce the exact same model as (2) if you couldn't fully control randomness but it should produce a model with comparable performance. Please submit these by January 15th, 2020. Wish you happy holidays and a very happy new year! Thanks, Imputation Challenge Organizers