HTA CRC Atlas 1

NOTE! This page is no longer updated, visit https://www.tissue-atlas.org/atlases/colorectal-cancer for the latest information

The HTA CRC Atlas 1 dataset contains images and other data being used for construction of an atlas of human colorectal cancer under the auspices of the Human Tumor Atlas Network. Advanced solid cancers are complex assemblies of tumor, immune, and stromal cells that invade adjacent tissue and spread to distant sites. We use highly multiplexed tissue imaging, spatial statistics, and machine learning to identify cell types and states underlying morphological features of known diagnostic and prognostic significance in colorectal cancer. This includes the tumor invasive margin, where tumor, normal, and immune cells compete and were diverse immunosuppressive environments are found.

Contents

Data overviews

NOTE! These Data Overviews provide access to minimally processed Level 2 images with no annotation or quality control. Click any of the following thumbnail images for an interactive view of the full-resolution images.

CRC01 – H&E
CRC01 – CYCIF
CRC02 – H&E
CRC02 – CYCIF
CRC03 – H&E
CRC03 – CYCIF
CRC04 – H&E
CRC04 – CYCIF
CRC05 – H&E
CRC05 – CYCIF
CRC06 – H&E
CRC06 – CYCIF
CRC07 – H&E
CRC07 – CYCIF
CRC08 – H&E
CRC08 – CYCIF
CRC09 – H&E
CRC09 – CYCIF
CRC10 – H&E
CRC10 – CYCIF
CRC11 – H&E
CRC11 – CYCIF
CRC12 – H&E
CRC12 – CYCIF
CRC13 – H&E
CRC13 – CYCIF
CRC14 – H&E
CRC14 – CYCIF
CRC15 – H&E
CRC15 – CYCIF
CRC16 – H&E
CRC16 – CYCIF
CRC17 – H&E
CRC17 – CYCIF
CRC18 – H&E

Data Explorations

CRC01 – INTRODUCTION

About Minerva

Exploring the primary image data in Lin-Wang-Sorger et al.

The images in Lin et al. (2021) comprise a ~4.5 TB dataset with some images as large as 1 gigapixel. We provide access to this information without restriction (as required by the NCI Moonshot effort) but it is not in a convenient form for reviewers or general users to explore. The open source Minerva software was designed for the Human Tumor Atlas Network (HTAN) by the Laboratory of Systems Pharmacology to address this problem.

Minerva enables intuitive real-time exploration of very large (gigapixel) high-plex images in the cloud using a web browser. With Minerva, users can pan around and magnify areas of an image and switch between channels. Minerva does not require the installation of any software and is therefore secure; browsing is also anonymous. Users interested in the tool are welcome to explore the documentation, the software publication, and a description of digital docents in general.

We provide two types of Minerva stories with this paper:

  1. “Data Overviews” provide access to minimally processed Level 2 images with annotation and interpretation kept to a bare minimum.
  2. “Data Explorations” are like museum guides and exploit the digital docents in Minerva to guide readers through the complexities of a large image dataset via a series of narrated stories and waypoints. Both written and audio narration are supported, as well as free exploration. These will be linked to individual figure panels in the final manuscript.