Datasets

The scientific process is often thought of as self-correcting. Scientists confirm or refute each other's results improving our understanding of the systems being studied. In practice, this requires a concerted effort, and in a non-negligible number of cases reproducing results is not done or may not even be possible. This has often been referred to as the replication or reproducibility crisis. Conducting research using an open science approach aims to address this issue, while at the same time increasing the pace of scientific discoveries and lowering costs. Sharing data is one of the key elements of the open science approach.

These datasets are shared to allow others to reproduce research results and possibly enable new research which we have not thought of. If you find this data useful in your work, please cite it using its DOI, when available, and the associated publication, if relevant.

This page uses javascript to expand and collapse the dataset descriptions (click the "description" link to expand/collapse it).

Microscopy

• "Accompanying dataset for: A Multi-scale, Multiomic Atlas of Human Normal and Follicular Lymphoma Lymph Nodes", A. Radtke et al., 2022 [description, download, associated publication].

  This dataset contains the processed scRNA-seq information from human lymph nodes, both normal and from Follicular Lymphoma (FL) patients analyzed in this work as a Seurat object. The scRNA-seq information was saved in the rds format for viewing and analysis using the R programming language (to load it in R: scrna_seq_data <- readRDS("scRNA_seq_data_object.rds")).

  Additionally, the dataset contains comma-separated-value tables describing human lymph nodes, both normal and from Follicular Lymphoma (FL) patients. The files are formatted using the anatomical structures (AS), cell types (CT), and biomarkers (B), ASCT+B format defined by the Human BioMolecular Atlas Program (HuBMAP) for use with the Reporter visualization tool. Details on the structure of ASCT+B tables and the Reporter tool can be found in the standard operating procedure authored by the ASCT+B working group.

• "Iterative Bleaching Extends multipleXity (IBEX) 2D and 3D Microscopy Data", A. Radtke et al., 2021 [description, download, associated publication].

  These datasets were acquired using the Iterative Bleaching Extends multi-pleXity (IBEX) imaging method. Acquisition of 3D data utilized the manual protocol while acquisition of the 2D data utilized the automated protocol. All data is stored using the Imaris file format. To view these multi-channel images, you can either use one of these free viewers, Imaris viewer, Fiji:

  1. Human Spleen (Manual)
  2. Human Liver (Manual)
  3. Human Kidney (Automated)
• "Accompanying dataset for: IBEX: An iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues", A. Radtke et al., 2021 [description, download, associated publication].

  These datasets were acquired using either the manual or automated IBEX multiplex imaging protocols. All image data are stored using the Imaris file format. To view these multi-channel images, you can either use one of these free viewers, Imaris viewer, Fiji:

  1. Human Jejunum (Automated)
  2. Human Kidney (Automated)
  3. Human Lymph Node (Automated)
  4. Human Skin (Automated)
  5. Human Liver (Manual)
  6. Human Lymph Node (Manual)
  7. Human Spleen (Manual)
• "Iterative Bleaching Extends multipleXity (IBEX) imaging method, mouse spleen", A. Radtke et al., 2020 [description, download, associated publication]

  This dataset is comprised of a three cycle IBEX experiment performed on mouse spleen sections labeled with the nuclear marker JOJO-1 and membrane label CD4 AF594. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 mm), y (0.284 mm), and z (1 mm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Files are in nrrd format.

  Markers per channel in each of the three cycles:

  1. spleen_panel1.nrrd (6 channels): B220 PE, CD8 BV421, IgD AF700, CD4 AF594, JOJO, Foxp3 eF660
  2. spleen_panel2.nrrd (7 channels): CD169 PE, F480 BV421, MHCII AF700, CollIV AF488, JOJO, CD11c AF647, CD4 AF594
  3. spleen_panel3.nrrd (7 channels): CD31 PE, CD68 BV421, Ki67 AF700, CD45 AF488, CD4 AF594, JOJO, CD3 AF647

Medical

• "Image-Guided Navigation: A Cost Effective Practical Introduction using the Image-Guided Surgery Toolkit (IGSTK)", O. Guler, Z. Yaniv, 2012 [description, download, associated publication].

  This data includes 10 phantom imaging studies acquired with a CT (humerus, pelvis, shoulder, vertebra, two different skull models, abdomen and three LEGO models). Each of the anatomical datasets includes its CT scan, the specific details of the model, a set of anatomical landmarks localized in the CT and a picture of the plastic model. For the LEGO phantom, each dataset includes its CT scan and the instructions on how to build it.

• "Localizing Spherical Fiducials in C-arm Based Cone-Beam CT", Z. Yaniv, 2009 [description, download, associated publication].

  This data includes two phantom imaging studies acquired with a Cone-Beam CT (CBCT) system. Each of the two datasets includes projection images (cine loops) and 3D reconstructions. Additionally, the data includes the CBCT system's projection matrices and MATLAB code for reading the projection images and overlaying epipolar lines onto them. All images are stored in the DICOM format.

General

• "Pill Image Data", T. S. Yoo et al., 2016 [description, download, associated publication].

  This dataset is comprised of digitial pictures of more than 4000 unique prescription pills, both capsules and tablets. A high resolution image of both sides of each product was acquired under laboratory lighting conditions, from a camera directly above, using specialized digital macro-photography techniques. Additional images using standard quality cameras (cell-phone or webcam) from a variety of angles were also acquired. In total the dataset includes 4000 high quality, reference, images and 133,000 standard quality images.