<p>After much research I found out how to obtain the annotations.</p>

<p>You must go to the REMC website: <a href="https://egg2.wustl.edu/roadmap/web_portal/" rel="nofollow noreferrer">https://egg2.wustl.edu/roadmap/web_portal/</a></p>

<p>Go to the chromatin-state-learning tab, and choose the n-chromatin state model desired - the core has 15 states, then 18, then 25 (imputed states). </p>

<p>Following this, you must go to the download URL link and, you will find a lot of files, primarily with the following coding information: E0*.. This corresponds to a particular tissue/cell type and so you must choose the one relevant to your research question. The way they are correspond to each tissue/cell type can be found in the following paper:</p>

<p><a href="https://www.nature.com/articles/s41467-019-11874-7#Sec22" rel="nofollow noreferrer">https://www.nature.com/articles/s41467-019-11874-7#Sec22</a></p>

CC BY-SA 4.0
2020-03-17T14:17:50.473Z
2020-03-17T15:20:12.513Z
2020-03-17T15:20:12.513Z
h3ab74
<p>I have been trying to use a pipeline for predicting gene expression for a target gene (Although you can do it for many) - the name of this method is epiXcan. Here is a link to the paper: </p>

<p><a href="https://www.nature.com/articles/s41467-019-11874-7#Sec22" rel="nofollow noreferrer">https://www.nature.com/articles/s41467-019-11874-7#Sec22</a></p>

<p>One of the very first steps in the pipeline is obtaining SNP 'annotations' from an epigenome reference consortium known as the REMC. In the methods paper they say: </p>

<p>"We first prepare eQTL statistics (computed with MatrixEQTL4) and SNP annotations (extracted from REMC <a href="https://egg2.wustl.edu/roadmap/web_portal/" rel="nofollow noreferrer">https://egg2.wustl.edu/roadmap/web_portal/</a>). For each eQTL tissue, we use the matched REMC tissue to
extract the corresponding annotations".</p>

<p>I have completed the first step of obtaining eQTL statistics. However obtaining SNP annotations is where I am lost. </p>

<p>In my case, I am only trying to predict the expression of one gene (DRD4) and so my region of interest is the pre-frontal cortex. If you visit the website they provide though, it doesn't seem as though annotating a large list of SNPs - at least in the way they are presenting - is possible. </p>

<p>Can anyone provide some insight or direction on how to proceed? How does one obtain SNP annotations from the REMC? I have tried emailing the authors of the paper and they have not been responsive.</p>

<p>Thank you,</p>

<sequence-annotation><snp><transcriptome><imputation>
REMC SNP annotations for transcriptome prediction - epiXcan
# REMC SNP annotations for transcriptome prediction - epiXcan

(Asked by: username_0 on 2020-03-11)

I have been trying to use a pipeline for predicting gene expression for a target gene (Although you can do it for many) - the name of this method is epiXcan. Here is a link to the paper:

<https://www.nature.com/articles/s41467-019-11874-7#Sec22>

One of the very first steps in the pipeline is obtaining SNP 'annotations' from an epigenome reference consortium known as the REMC. In the methods paper they say:

"We first prepare eQTL statistics (computed with MatrixEQTL4) and SNP annotations (extracted from REMC <https://egg2.wustl.edu/roadmap/web_portal/>). For each eQTL tissue, we use the matched REMC tissue to
extract the corresponding annotations".

I have completed the first step of obtaining eQTL statistics. However obtaining SNP annotations is where I am lost.

In my case, I am only trying to predict the expression of one gene (DRD4) and so my region of interest is the pre-frontal cortex. If you visit the website they provide though, it doesn't seem as though annotating a large list of SNPs - at least in the way they are presenting - is possible.

Can anyone provide some insight or direction on how to proceed? How does one obtain SNP annotations from the REMC? I have tried emailing the authors of the paper and they have not been responsive.

Thank you,

**Tags:** sequence-annotation, snp, transcriptome, imputation

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## 1 answers

### Answer by username_0 on 2020-03-17. Score: 0 | Accepted answer

After much research I found out how to obtain the annotations.

You must go to the REMC website: <https://egg2.wustl.edu/roadmap/web_portal/>

Go to the chromatin-state-learning tab, and choose the n-chromatin state model desired - the core has 15 states, then 18, then 25 (imputed states).

Following this, you must go to the download URL link and, you will find a lot of files, primarily with the following coding information: E0\*.. This corresponds to a particular tissue/cell type and so you must choose the one relevant to your research question. The way they are correspond to each tissue/cell type can be found in the following paper:

<https://www.nature.com/articles/s41467-019-11874-7#Sec22>


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