Yu-AnChen

# @File(label="Select a slide to process") filename
# @File(label="Select the output location", style="directory") output_dir
# @String(label="Experiment name (base name for output files)") experiment_name
# @Float(label="Flat field smoothing parameter (0 for automatic)", value=0.1) lambda_flat
# @Float(label="Dark field smoothing parameter (0 for automatic)", value=0.01) lambda_dark

# Takes a slide (or other multi-series BioFormats-compatible file set) and
# generates flat- and dark-field correction profile images with BaSiC. The
# output format is two multi-series TIFF files (one for flat and one for dark)
# which is the input format used by Ashlar.

Yu-AnChen

import pytiff
import skimage.io

try:
    import pathlib
except ImportError:
    import pathlib2 as pathlib
import argparse
import warnings
import sys

Yu-AnChen

The following instructions take you through setting up a SSH Key on O2. (Official instructions for generating SSH key)

The senario behind this is that in CyCIF pipeline, it is designed to first submit a job to transfer files from /n/files, get the job ID, and the following steps in the pipeline are dependent on the transfer job.

And the SSH Key allows you to transfer files from /n/files using the transfer server with ssh rsync, without being prompted for password. So that you can put ssh rsync from n/files to /n/scratch2 into an sbatch script. And the job could hang until the transfer is complete, then it will run the rest of the script.

Note: Replace your_ecommons with your ecommons while you type in the commands.

---

Yu-AnChen

#
# deepzoom_tile - Convert whole-slide images to Deep Zoom format
#
# Copyright (c) 2010-2015 Carnegie Mellon University
#
# This library is free software; you can redistribute it and/or modify it
# under the terms of version 2.1 of the GNU Lesser General Public License
# as published by the Free Software Foundation.
#
# This library is distributed in the hope that it will be useful, but

Yu-AnChen

from __future__ import print_function
import csv
from subprocess import call
try:
    import pathlib
except ImportError:
    import pathlib2 as pathlib
import argparse
import os
from bin_rcpnl_module import *

Yu-AnChen

from __future__ import print_function
import csv
from subprocess import call
try:
    import pathlib
except ImportError:
    import pathlib2 as pathlib
import argparse
import os
from ashlar import reg, thumbnail

Yu-AnChen

Tools

1. convert .rcpnl file to .ome.tif using
   bfconvert sample.rcpnl sample.ome.tif

2. extract XML from converted .ome.tif file using
   tiffcomment sample.ome.tif > output_metadata.xml

3. edit output_metadata.xml using text editor

Yu-AnChen

from __future__ import print_function
import csv
from subprocess import call
try:
    import pathlib
except ImportError:
    import pathlib2 as pathlib
import argparse
import os
from ashlar import find_cycle_offset

Yu-AnChen

# @File(label="Select a slide to process") filename
# @File(label="Select the output location", style="directory") output_dir
# @String(label="Experiment name (base name for output files)") experiment_name
# @Integer(label="Rows", value=10) rows
# @Integer(label="Columns", value=10) cols

# Takes a slide (or other multi-series BioFormats-compatible file set) and
# generates flat- and dark-field correction profile images with BaSiC. The
# output format is two multi-series TIFF files (one for flat and one for dark)
# which is the input format used by Ashlar.

Yu-AnChen

Exemplar - run ASHLAR on demo data with the batch script

1. Download and unzip FIJI, move the FiJji.app folder to C:\Users\Public\Downloads\

2. Install BaSiC by following the instructions under the Install via the Fiji Updater section on this page

3. Save the imagej_basic_ashlar.py to C:\Users\Public\Downloads\Fiji.app\plugins\

4. Launch command prompt