GTEx v8 fine mapping on eQTL and sQTL

# Data usage policy When using this data, you must acknowledge the source by citing the publication "Widespread dose-dependent effects of RNA expression and splicing on complex diseases and traits" (https://doi.org/10.1101/814350). # GTEx-GWAS integration: Finemapping This package contains DAP-G results on GTEx v8 eQTL and sQTL data.<br> See ([DAP-G software](https://github.com/xqwen/dap)) for details.<br> We used only European individuals and variants with MAF&gt;0.01, on genes that are annotated as `protein_coding` or `lncRNA`. <br> DAP-G `ld_control` parameter was 0.75. The results were analyzed in [this preprint](https://www.biorxiv.org/content/10.1101/814350v1) ## Contents ```<br> finemapping/<br> |-- README_finemapping.md<br> |-- dapg_eqtl.tar<br> `-- dapg_sqtl.tar<br> ```<br> Unpack each tarball with a command like `tar -xvpf dapg_sqtl.tar` For every tissue: * `{tissue}.variants_pip.txt.gz` contains the variants' posterior inclusion probabilities at being causal for every gene.<br> * gene: gene id (or intron id)<br> * rank: ranking of the variant according to its PIP (see below)<br> * variant_id: gtex variant id<br> * pip: posterior inclusion probability of the variant in the causal models<br> * log10_abf: approximate Bayes factor (-log10)<br> * cluster_id: id of cluster to which the variant belongs <br> * `{tissue}.models_variants.txt.gz` contains, for every model contemplated by DAPG, the list of variants involved. Most of them have single variant.<br> * `{tissue}.model_summary.txt.gz` contains, for every analized gene, a summary of the modes such as expected number of causal variants<br> * gene: gene id (or intron id)<br> * pes: posterior expected model size (i.e. number of causal variants)<br> * pse_se: standard error of the above<br> * log_nc: dapg undocumented statistic<br> * log10_nc: dapg undocumented statistic<br> * `{tissue}.models.txt.gz` for every analyzed gene:<br> * gene: gene id (or intron id)<br> * model: number (serving as a model name)<br> * n: number of variants (0 for null model)<br> * pp: posterior inclusion probability of the model<br> * ps: posterior score<br> * `{tissue}.clusters.txt.gz` for every analyzed gene:<br> * gene: gene id (or intron id)<br> * cluster: number (serving as cluster name)<br> * n_snps: number of variants in the cluster<br> * pip: posterior inclusion probability<br> * average_r2: average correlation within the cluster<br> * `{tissue}.cluster_correlations.txt.gz`: upper triangular matrix of correlations among clusters # Disclaimer The data is provided "as is", and the authors assume no responsibility for errors or omissions. <br> The User assumes the entire risk associated with its use of these data. <br> The authors shall not be held liable for any use or misuse of the data described and/or contained herein. <br> The User bears all responsibility in determining whether these data are fit for the User's intended use. The information contained in these data is not better than the original sources from which they were derived,<br> and both scale and accuracy may vary across the data set. <br> These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics<br> appropriate for applications that potential users of the data may contemplate. <br> <br> The user is responsible to comply with any data usage policy from the original GWAS studies;<br> refer to the list of traits described [here](https://www.biorxiv.org/content/10.1101/814350v1)<br> to identify their respective Consortia's requirements. <br> THE DATA IS PROVIDED WITHOUT WARRANTY OF ANY KIND,<br> EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,<br> FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.<br> IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,<br> WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,<br> OUT OF OR IN CONNECTION WITH THE DATA OR THE USE OR OTHER DEALINGS IN THE DATA.

# 数据使用政策
使用本数据集时，您必须通过引用以下文献来注明来源：《Widespread dose-dependent effects of RNA expression and splicing on complex diseases and traits》（链接：https://doi.org/10.1101/814350）。

# GTEx与全基因组关联分析（Genome-Wide Association Study, GWAS）整合：精细定位
本数据包包含针对GTEx v8版表达数量性状位点（expression Quantitative Trait Loci, eQTL）和剪接数量性状位点（splicing Quantitative Trait Loci, sQTL）数据的DAP-G分析结果。
详细信息请参阅[DAP-G软件](https://github.com/xqwen/dap)。
本分析仅纳入欧洲血统个体、次要等位基因频率（Minor Allele Frequency, MAF）大于0.01的变异，以及注释为`protein_coding`（蛋白编码基因）或`lncRNA`（长链非编码RNA）的基因。
本次分析中DAP-G的`ld_control`参数设为0.75。本数据集的分析结果已在[该预印本](https://www.biorxiv.org/content/10.1101/814350v1)中进行阐述。

## 内容结构

finemapping/
├── README_finemapping.md
├── dapg_eqtl.tar
└── dapg_sqtl.tar

可使用类似`tar -xvpf dapg_sqtl.tar`的命令解压每个压缩包文件。

针对每个组织：
* `{tissue}.variants_pip.txt.gz`：包含各变异针对对应基因的因果关联后验包含概率（posterior inclusion probability, PIP）。
* `gene`：基因ID（或内含子ID）
* `rank`：基于变异的后验包含概率（PIP）进行的排序
* `variant_id`：GTEx变异ID
* `pip`：变异在因果模型中的后验包含概率
* `log10_abf`：近似贝叶斯因子的负对数10转换值（即$-log_{10}(ABF)$）
* `cluster_id`：变异所属的簇ID

* `{tissue}.models_variants.txt.gz`：包含DAP-G所考虑的每个因果模型涉及的变异列表，其中多数模型仅包含单个变异。

* `{tissue}.model_summary.txt.gz`：包含每个分析基因的模型汇总信息，例如因果变异的期望数目。
* `gene`：基因ID（或内含子ID）
* `pes`：后验期望模型大小（即因果变异的期望数目）
* `pse_se`：上述后验期望模型大小的标准误
* `log_nc`：DAP-G的未公开统计量
* `log10_nc`：DAP-G的未公开统计量（log10转换形式）

* `{tissue}.models.txt.gz`：针对每个分析基因，包含以下内容：
* `gene`：基因ID（或内含子ID）
* `model`：模型编号（用作模型名称）
* `n`：模型包含的变异数目（空模型取值为0）
* `pp`：该模型的后验包含概率
* `ps`：后验评分

* `{tissue}.clusters.txt.gz`：针对每个分析基因，包含以下内容：
* `gene`：基因ID（或内含子ID）
* `cluster`：簇编号（用作簇名称）
* `n_snps`：该簇包含的变异数目
* `pip`：该簇的后验包含概率
* `average_r2`：簇内变异间的平均相关系数

* `{tissue}.cluster_correlations.txt.gz`：簇间相关系数的上三角矩阵

## 免责声明
本数据集按“现状”提供，作者不对数据中的错误或遗漏承担任何责任。
使用者需自行承担使用本数据集的全部风险。
作者不对本数据集的任何使用或误用承担法律责任。
使用者需自行判断本数据集是否符合其特定使用需求。
本数据集所包含的信息并未优于其原始来源，数据集的覆盖范围与准确性可能存在差异。
本数据集可能不具备潜在使用者所设想的应用所需的准确性、分辨率、完整性、时效性或其他相关特性。

使用者需遵守原始全基因组关联分析（GWAS）研究的数据使用政策；可参阅[此处](https://www.biorxiv.org/content/10.1101/814350v1)列出的性状列表，以了解对应联盟的具体要求。

本数据集不提供任何形式的明示或默示担保，包括但不限于适销性、特定用途适用性以及不侵权的担保。
在任何情况下，作者或版权持有人均不对因使用本数据集而产生的任何索赔、损害或其他责任承担责任，无论该责任源于合同、侵权行为或其他事由，亦无论该责任与数据集使用或其他相关操作直接或间接相关。