癌症组学药物实验反应数据集

数据集获取

git clone https://github.com/PNNL-CompBio/coderdata.git

curl -L -o repo.zip https://github.com/PNNL-CompBio/coderdata/archive/refs/heads/main.zip
unzip repo.zip

源站 README 摘录（使用方式）

Cancer Omics Drug Experiment Response Dataset

There is a recent explosion of deep learning algorithms that to tackle the computational problem of predicting drug treatment outcome from baseline molecular measurements. To support this,we have built a benchmark dataset that harmonizes diverse datasets to better assess algorithm performance.
This package collects diverse sets of paired molecular datasets with corresponding drug sensitivity data. All data here is reprocessed and standardized so it can be easily used as a benchmark dataset for the
This repository leverages existing datasets to collect the data
required for deep learning model development. Since each deep learning model
requires distinct data capabilities, the goal of this repository is to
collect and format all data into a schema that can be leveraged for
existing models.
coderdata develompent")
The goal of this repository is two-fold: First, it aims to collate and
standardize the data for the broader community. This requires
running a series of scripts to build and append to a standardized data
model. Second, it has a series of scripts that pull from the data
model to create model-specific data files that can be run by the data
infrastructure.

Data access

For the access to the latest version of CoderData, please visit our
documentation site which provides access to Figshare and
instructions for using the Python package to download the data.

Data format

All coderdata files are in text format - either comma delimited or tab
delimited (depending on data type). Each dataset can be evaluated
individually according to the CoderData schema that is maintained in LinkML
and can be udpated via a commit to the repository. For more details,
please see the schema description.

Building a local version

The build process can be found in our coderbuild
directory. Here you can follow the instructions to
build your own local copy of the data on your machine.

Adding a new dataset

We have standardized the build (coderbuild) process so an additional dataset can be
built locally or as part of the next version of coder. Here are the
steps to follow:

1. First visit the coderbuild
   directory and ensure you can build a local copy of
   CoderData.

2. Checkout this rep

完整仓库：github.com/PNNL-CompBio/coderdata