DOI: 10.6078/d1m13b
title: 3D micro-CT image of cichlid fish samples for genetic analysis

description: The number of Genome-Wide Association Studies (GWAS) has been growing
 rapidly in recent years due to developments in genotyping and sequencing
 platforms. When applied to quantitative traits, these and other
 statistical genetics approaches require large amounts of consistently and
 accurately measured phenotypes. Using the data shared here, we
 introduce a computational toolbox based on deep convolutional neural
 networks that we have developed to phenotype quantitative traits
 describing morphology from micro-CT-scan image datasets. We
 illustrate the use of this Deep Learning Phenotyper (DLP) on a sample set
 of craniofacial CT scans of 118 samples from two very closely related
 species of Lake Malawi cichlid fish, Maylandia zebra and Cynotilapia
 zebroides. We show that the pipeline constructed and implemented here is
 capable of measuring morphological skeletal phenotypes with high accuracy.
 We also demonstrate how this pipeline can be integrated with existing GWAS
 frameworks to identify candidate association loci. We believe the methods
 we present here will be valuable for groups studying quantitative
 morphological traits not only in fishes, but in other vertebrates using CT
 scan datasets. The data shared here is an example dataset containing both
 the primary CT data for a sample (as an Anterior-Posterior image stack),
 and the denoised and compressed image stacks in all three orientations
 (AP, Left-Right, and Dorsal-Ventral) which are generated by the initial
 preprocessing steps described in the paper.
description: The data was collected through three field trips to Lake Malawi,
 where fish samples were collected from four different locations: 1)Thumbi
 West, 2) Nkhata Bay, 3)Otter Point, and 4) Chiofu. The fish collected were
 then brought to the University of Cambridge, where they were fixed in
 formaldehyde and ethanol, and scanned at the Cambridge Biotomography
 Centre using a Nikon XT 225 ST micro-CT scanner. 
description: # ZebraAfra The data provided here is an example image stack for a
 *Maylandia zebra* fish sample. The image stack for both the raw CT scan
 projections and the computed tomography images are provided in the
 Anterior-Posterior projection. These raw images were pre-processed using
 the pipeline described in our paper and three sets of image stacks were
 generated for each standard projection: Anterior-Posterior (AP),
 Left-Right (LR), and Dorsal-Ventral (DV). ## Description of the Data and
 file structure The main directory contains the following directories,
 within which the processed and raw data files are stored: 1. Raw images 1.
 CentreSlice 1. Sinogram - Contains the Sinogram images used for
 backpropagation 2. D25-E10 Skull.ct2dprofile.xml - Contains the
 specifications of the CT scanner such as the voxel sizes, offset of
 scanner and X-ray source, etc 3. D25-E10 Skull.xtek2dct - Contains the
 specifications of the CT scanner such as the voxel sizes, offset of
 scanner and X-ray source, etc 2. D25-E10 Skull\_01 1. [vg-project] D25-E10
 Skull - Contains the VGP files that specify the structure of the data when
 images are opened with different softwares 2. D25-E10 Skull\_0000.tif -
 D25-E10 Skull\_1888.tif - All the computed tomography images generated
 through back-calculation of X-ray absorption. 3. D25-E10 Skull.vgl - The
 VGL file that specify the structure of the data when images are opened
 with different softwares 3. D25-E10 Skull\_0001.tif - D25-E10
 Skull\_1081.tif - All the raw projections that were collected by the CT
 scanner through rotations around the fish. 4. D25-E10 Skull.xtekct -
 Contains the specifications of the CT scanner such as the voxel sizes,
 offset of scanner and X-ray source, etc 5. \_ctdata.txt - This file
 specifies the number of projections and the angle between them that the
 scanner has used to generate raw projections. 6. D25-E10
 Skull.ctprofile.xml - Contains the specifications of the CT scanner such
 as the voxel sizes, offset of scanner and X-ray source, etc 2.
 D25-E10\_180613-processed-AP 1. D25-E10 Skull\_0000.jpg - D25-E10
 Skull\_1888.jpg - All the compressed, de-noised, and processed images for
 the same fish along the Anterior-Posterior axis. 3.
 D25-E10\_180613-processed-LR 1. 0001.jpg - 1239.jpg - All the compressed,
 de-noised, and processed images for the same fish along the Left-Right
 axis. 4. D25-E10\_180613-processed-DV 1. 0001.jpg - 2000.jpg - All the
 compressed, de-noised, and processed images for the same fish along the
 Dorsal-Ventral axis. ## Sharing/Access Information This example data set
 is publicly available for anyone to download, view, and use to run the DLP
 pipeline we developed.