Ashlar performs fast, high-quality stitching of microscopy images. It also co-registers multiple rounds of cyclic imaging for methods such as CyCIF and CODEX. Ashlar can read image data directly from BioFormats-supported microscope vendor file formats as well as a directory of plain TIFF files. Output is saved as pyramidal, tiled OME-TIFF.
Note that Ashlar requires unstitched individual "tile" images as input, so it is not suitable for microscopes or slide scanners that only provide pre-stitched images.
Visit labsyspharm.github.io/ashlar/ for the most up-to-date information on ASHLAR.
ashlar [-h] [-o PATH] [-c CHANNEL] [--flip-x] [--flip-y]
[--flip-mosaic-x] [--flip-mosaic-y]
[--output-channels [CHANNEL [CHANNEL ...]]] [-m SHIFT]
[--filter-sigma SIGMA] [-f FORMAT] [--pyramid]
[--tile-size PIXELS] [--ffp [FILE [FILE ...]]]
[--dfp [FILE [FILE ...]]] [--plates] [-q] [--version]
FILE [FILE ...]
Stitch and align one or more multi-series images
positional arguments:
FILE an image file to be processed (one file per cycle)
optional arguments:
-h, --help show this help message and exit
-o PATH, --output PATH
write output to PATH; default is
ashlar_output.ome.tif. If value ends in .ome.tif an
OME-TIFF with tiled image pyramid will be written. If
value ends in just .tif and includes {cycle} and
{channel} placeholders a series of single-channel TIFF
files will be written. Otherwise value will be
interpreted as a directory and the '-f' and '--
pyramid' arguments will control the file names and
format.
-c CHANNEL, --align-channel CHANNEL
align images using channel number CHANNEL; numbering
starts at 0
--flip-x flip tile positions left-to-right to account for
unusual microscope configurations
--flip-y flip tile positions top-to-bottom to account for
unusual microscope configurations
--flip-mosaic-x flip output image horizontally
--flip-mosaic-y flip output image vertically
--output-channels [CHANNEL [CHANNEL ...]]
output only channels listed in CHANNELS; numbering
starts at 0
-m SHIFT, --maximum-shift SHIFT
maximum allowed per-tile corrective shift in microns
--filter-sigma SIGMA width in pixels of Gaussian filter to apply to images
before alignment; default is 0 which disables
filtering
-f FORMAT, --filename-format FORMAT
use FORMAT to generate output filenames, with {cycle}
and {channel} as required placeholders for the cycle
and channel numbers; default is
cycle_{cycle}_channel_{channel}.tif (DEPRECATED: Use
the '-o' argument to specify the output filename
format.)
--pyramid write output as a single pyramidal OME-TIFF
--tile-size PIXELS set tile width and height to PIXELS (pyramid output
only); default is 1024
--ffp [FILE [FILE ...]]
read flat field profile image from FILES; if specified
must be one common file for all cycles or one file for
each cycle
--dfp [FILE [FILE ...]]
read dark field profile image from FILES; if specified
must be one common file for all cycles or one file for
each cycle
--plates enable plate mode for HTS data
-q, --quiet suppress progress display
--version print version
Ashlar can be installed in most Python environments using pip:
pip install ashlarIf you don't already have miniconda or Anaconda, download the python 3.x version and install. Then, run the following commands from a terminal (Linux/Mac) or command prompt (Windows):
Create a named conda environment with python 3.7:
conda create -y -n ashlar python=3.7Activate the conda environment:
conda activate ashlarIn the activated environment, install dependencies and ashlar itself:
conda install -y -c conda-forge numpy scipy matplotlib networkx scikit-image=0.16.2 scikit-learn tifffile zarr pyjnius=1.2.1
pip install ashlarThe docker image of ashlar is on DockerHub at labsyspharm/ashlar which should be
suitable for many use cases.
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