Cultures of healthy and ALS iPSCs-derived motor neurons immunolabeled for Beta Tubulin III and TDP-43 and counterstained with DAPI

The archive (<strong>fluoMNs_subset.zip</strong>) contains five folders corresponding to five screens: E, F, G, H and I. Each screen has one or several folders corresponding to one or several plates. The content of the archive is annotated in <strong>annotations_fluoMNs_subset.csv.</strong> Each row corresponds to one field of fiew in the 96-well plates. Each well in the plate has 10 to 12 fields of view, each field of view has 4 to 5 planes and each plane was stained with 3 to 4 channels. Each image is encoded as follows: <em>00<strong>R</strong>00<strong>C</strong>-<strong>F</strong>-00100<strong>P</strong>00<strong>H</strong></em>, where <strong><em>R</em></strong> is the row of the well in the plate, <strong><em>C</em></strong> is the column of the well in the plate, <strong><em>F</em></strong> is the field of view, <strong><em>P</em></strong> is the plane and <strong><em>H</em></strong> is the channel. Here are two Python functions to get the complete path to one image: <pre><em>def </em>get_filename(source_directory, <em>experiment</em>: str, <em>plate</em>: str, <em>image_id</em>: str) -&gt; str: """Return pathname of an image""" <em>return </em>f'{source_directory}/{<em>experiment</em>}/{<em>plate</em>}/{<em>image_id</em>}.tif' <em>def </em>get_image_id(<em>row</em>: int, <em>col</em>: int, <em>fov</em>: int, <em>plane</em>: int, <em>channel</em>: int) -&gt; str: """Return id of an image""" <em>return </em>f'{<em>row</em>:03}{<em>col</em>:03}-{<em>fov</em>}-001{<em>plane</em>:03}{<em>channel</em>:03}'</pre> This is a subset of a larger dataset of cultures of motor neurons under different celullar stress and immunolabeled for ALS-linked RNA-binding proteins. The whole dataset (~1TB) is available on IDR. Some code using this data subset for classification of ALS vs healthy motor neurons can be accessed on Github. This data has been used in a manuscript posted on BioRxiv.