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#!/usr/bin/env nextflow

// Demonstration of hierarchical scatter/gather in Nextflow

// Tasks have two pieces of meta a chr (chromosome) and a reg (sub-
// chromosomal region). The workflow includes a step which gathers
// of all regions for a chromosome.
//
// The process phase_region is fast when chr in {"chr1", "chr2"} and slow
// when chr == "chr3". The gather process for distinct chromosomes

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#!/usr/bin/env bash
set -eo pipefail


THREADS=8

usage="
DeepVariant genotyping of medaka variants.

First run:

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/* The MIT License

   Permission is hereby granted, free of charge, to any person obtaining
   a copy of this software and associated documentation files (the
   "Software"), to deal in the Software without restriction, including
   without limitation the rights to use, copy, modify, merge, publish,
   distribute, sublicense, and/or sell copies of the Software, and to
   permit persons to whom the Software is furnished to do so, subject to
   the following conditions:

cjw85

FROM ubuntu:18.04
RUN groupadd -g 1001 -r flappie && useradd -r -u 999 -g flappie flappie

# Install flappie
RUN apt-get update \
    && apt-get install -y libcunit1 libhdf5-100 libopenblas-base cmake libcunit1-dev libhdf5-dev libopenblas-dev git git-lfs \
    && git lfs install \
    && git clone https://github.com/nanoporetech/flappie \
    && cd flappie \
    && git lfs install \

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# Requirements: pip install numpy, pysam, scrappie
#
# usage: simulate_calls.py [-h] [--mu MU] [--sigma SIGMA] [--noise NOISE]
#                          [--threads THREADS]
#                          fasta ncalls
# 
# Simulate basecalls with scrappy.
#
# positional arguments:
#   fasta              Source sequence file.

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"""
Reimplementation of nanonet using keras.

Follow the instructions at
https://www.tensorflow.org/install/install_linux
to setup an NVIDIA GPU with CUDA8.0 and cuDNN v5.1.

virtualenv venv --python=python3
. venv/bin/activate
pip install numpy

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import numpy as np
import pickle

class MyArray(np.ndarray):
    """An np.ndarray subclass with attrs that behave nicely."""
    def __new__(cls, a, meta=None):
        obj = np.asarray(a).view(cls)
        obj.meta = meta
        return obj