# Downloading data

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If you have questions or feedback about the download tools provided by IDC, please reach out via our [forum](https://discourse.canceridc.dev/) - we are very interested in hearing your feedback and suggestions!
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IDC supports a variety of interfaces for fetching individual images, cohorts (groups of images), or portions of images, using desktop application, command-line interface, or programmatic API. These interfaces are covered in the subsequent pages. You should select the specific approach to accessing IDC data depending on your requirements.

* Download **directly from** [**IDC Portal**](/data/downloading-data/idc-portal.md): no prerequisites other than a Chrome web browser!
* [idc-index](https://learn.canceridc.dev/data/downloading-data/downloading-data#command-line-or-programmatic-download-idc-index-python-package) interface: **command-line and Python API interface** to download images corresponding to the specific patient/study/series, or a cohort defined by a manifest
* [3D Slicer](/data/downloading-data/downloading-data.md) interface: **desktop application** to download images corresponding to the specific patient/study/series, or a cohort defined by a manifest
* [s5cmd](/data/downloading-data/downloading-data-with-s5cmd.md): **command-line interface** to download images for a cohort defined by a manifest (unlike `idc-index`, does not organize downloaded images into folders corresponding to IDC data model hierarchy)
* [DICOMweb](/data/downloading-data/dicomweb-access.md) interface: **REST API interface** to access both metadata and pixel data at the granularity of image frames/tiles
* [Directly loading DICOM objects from Google Cloud or AWS in Python](/data/downloading-data/direct-loading.md): **Python API interface** to access both metadata and pixel data at the granularity of image frames/tiles


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# Agent Instructions: Querying This Documentation

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://learn.canceridc.dev/data/downloading-data.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.