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Posted to commits@airavata.apache.org by ma...@apache.org on 2019/06/02 17:22:59 UTC
[airavata-php-gateway] 12/14: updates for dTOX
This is an automated email from the ASF dual-hosted git repository.
machristie pushed a commit to branch dreg-gateway
in repository https://gitbox.apache.org/repos/asf/airavata-php-gateway.git
commit 40240074ee5731e8f4e42d77404659dc47e1436f
Author: root <ro...@dreg-gateway-instance1.jetstreamlocal>
AuthorDate: Thu Jan 17 22:16:22 2019 +0000
updates for dTOX
---
app/libraries/FileTransfer.php | 2 +-
app/views/partials/experiment-info.blade.php | 5 +-
public/themes/dreg/assets/img/dregicon.png | Bin 0 -> 2128 bytes
public/themes/dreg/assets/img/dtox.create.exp2.png | Bin 42088 -> 40049 bytes
public/themes/dreg/partials/dtox-doc.blade.php | 126 +++++++++------------
public/themes/dreg/partials/header.blade.php | 6 +-
public/themes/dreg/partials/software.blade.php | 16 ++-
public/themes/dreg/partials/template.blade.php | 14 ++-
8 files changed, 79 insertions(+), 90 deletions(-)
diff --git a/app/libraries/FileTransfer.php b/app/libraries/FileTransfer.php
index 470139c..1dd6dd9 100644
--- a/app/libraries/FileTransfer.php
+++ b/app/libraries/FileTransfer.php
@@ -120,7 +120,7 @@ class FileTransfer {
},'. "\n" ;
$content = $content . '{
- type:"bigwig",
+ type:"bedgraph",
url:"'.$protocol.'://'. $_SERVER['HTTP_HOST'] .'/gbfile/'.RBase64::encode( $folder_path . '/'. $out_prefix .'.dTOX.bound.bed.gz').'",
name: "dTOX bound status:",
mode: "show",
diff --git a/app/views/partials/experiment-info.blade.php b/app/views/partials/experiment-info.blade.php
index 4715e6d..1e88c0b 100644
--- a/app/views/partials/experiment-info.blade.php
+++ b/app/views/partials/experiment-info.blade.php
@@ -243,10 +243,7 @@ If the job is failed, please refer <A href="https://dreg.dnasequence.org/pages/d
@if(file_exists($dataRoot . '/' . $expDataDir. '/ARCHIVE/'.$param_prefix.'.tar.gz') )
<option value=<?php echo $param_prefix.".tar.gz" ?>>Full results</option>
@endif
-@if(file_exists($dataRoot . '/' . $expDataDir. '/ARCHIVE/'.$param_prefix.'.dTOX.full.bed.gz') )
- <option value=<?php echo $param_prefix.".dTOX.full.bed.gz"?>>all dTOX regions</option>
-@endif
-@if(file_exists($dataRoot . '/' . $expDataDir. '/ARCHIVE/'.$param_prefix.'.dTox.bound.bed.gz') )
+@if(file_exists($dataRoot . '/' . $expDataDir. '/ARCHIVE/'.$param_prefix.'.dTOX.bound.bed.gz') )
<option value=<?php echo $param_prefix.".dTOX.bound.bed.gz"?>>dTOX bound regions </option>
@endif
</select>
diff --git a/public/themes/dreg/assets/img/dregicon.png b/public/themes/dreg/assets/img/dregicon.png
new file mode 100644
index 0000000..1af0e6e
Binary files /dev/null and b/public/themes/dreg/assets/img/dregicon.png differ
diff --git a/public/themes/dreg/assets/img/dtox.create.exp2.png b/public/themes/dreg/assets/img/dtox.create.exp2.png
index c4d0843..5af3f6d 100644
Binary files a/public/themes/dreg/assets/img/dtox.create.exp2.png and b/public/themes/dreg/assets/img/dtox.create.exp2.png differ
diff --git a/public/themes/dreg/partials/dtox-doc.blade.php b/public/themes/dreg/partials/dtox-doc.blade.php
index d54bdea..cabdf82 100755
--- a/public/themes/dreg/partials/dtox-doc.blade.php
+++ b/public/themes/dreg/partials/dtox-doc.blade.php
@@ -37,27 +37,27 @@ Select the menu 'Start dREG/dTOX' below the dREG logo to create an data analysis
<p class="description" style="padding:16px">
4) <b>Fill experiment form</b><br>
-Select bigWig files representing PRO-seq, ATAC-seq, or dNase-I-seq signal on the plus and minus strand. Please notice that two GPU resources are available now, currently it is easier to get the computation resources on <A href="http://comet.sdsc.xsede.org/">Comet.sdsc.xsede.org</A> than <A href="https://www.psc.edu/index.php/bridges">Bridges.psc.edu</A>.
+Select bigWig files representing PRO-seq, ATAC-seq, or DNase-I-seq signal on the plus and minus strand.
</p>
<div style=" display: flex;justify-content: center"><img style="align-self: center;width:70%" alt="dREG experiment create" src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/dtox.create.exp2.png" ></img></div>
<p class="description" style="padding:16px">
5) <b>Submit the job</b><br>
-Click the 'save and launch' button. BigWig file are transferred to the XSEDE server and a GPU queue is scheduled to run dREG. After submitting, the user can check the status in the next web page, as shown below. Depend on the queue status, the job maybe wait for a long time to start prediction. Once started, it will only take 1-4 hours to complete.</p>
+Click the 'save and launch' button. BigWig file are transferred to the XSEDE server and a GPU queue is scheduled to run dTOX. After submitting, the user can check the status in the next web page, as shown below. Depending on the queue status, the job may wait for some time to start prediction. Once started, it will take 6-10 hours to complete depending on the genome used.</p>
<p class="description" style="padding:16px">
6) <b>Check the status</b><br>
-The user can check the status of their 'experiment' by clicking the menu 'Saved runs' below the dREG logo.
+The user can check the status of their 'experiment' by clicking the 'Saved runs' button on the top menu.
</p>
<div style=" display: flex;justify-content: center"><img style="align-self: center;width:70%" alt="dREG experiment browse" src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/dreg.exp.list.png"></img></div>
<p class="description" style="padding:16px">
7) <b>Check the results</b><br>
-Once a job is completed, the user can select 'Full results' in the drop-down list and then LEFT-click <B>'Download'</B> link in the experiment summary page to download a compressed file described in the <a href="#output" role="tab" data-toggle="tab">'output'</A> sheet in this page, or the user can download any single file from the drop-down list. The downloaded file with the 'tar.gz' extension can be decompressed by the 'tar' command, the file with the 'gz' extension can be decompressed [...]
+Once a job is completed, the user can select 'dTOX Bound Regions' in the drop-down list and then LEFT-click <B>'Download'</B> link in the experiment summary page to download a compressed file described in the <a href="#output" role="tab" data-toggle="tab">'output'</A> sheet in this page. The downloaded file has a 'gz' extension and can be decompressed by the 'gunzip' command in Linux. Please <font color="red">don't use RIGHT-click </font> to open a tab for downloading. To extract bound [...]
</br>
-In <font color="RED">Safari</font>, it could be problematic because Safari tries to unzip the compressed results automatically using a non-compatible compress method. Please check <A href="https://octet.oberlin.edu/does-your-mac-unzip-zip-files-automatically/"> this link </A> to disable this feature.</p>
+In <font color="RED">Safari</font>, it could be problematic because Safari tries to unzip the compressed results automatically using a non-compatible compression method. Please check <A href="https://octet.oberlin.edu/does-your-mac-unzip-zip-files-automatically/"> this link </A> to disable this feature.</p>
<div style=" display: flex;justify-content: center"><img style="align-self: center;width:70%" alt="dREG experiment summary" src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/dreg.exp.summary.png"></img></div>
@@ -76,9 +76,9 @@ The following figure shows the data files in the job's folder, including two big
<a name="failure"></a>
<p class="description" style="padding:16px">
- 10) <b>When you meet failure</b><br>
+ 10) <b>If your job fails</b><br>
-Currently when you run the dREG jobs, there are two types of errors you may have. One error may come from the system, called a system error, such as no computing time on specific GPU nodes or an internal errors in Apache Airavata. The other type of error is caused by the users' bigwig, called bigwig error, which can occur when read counts are normalized, each read is mapped to a region, or read counts in minus strand are positive values. The following figures show how to identify the err [...]
+When you run dTOX, there are two main types of errors you may encounter. One error may come from the system, called a system error, such as no computing time on specific GPU nodes or an internal errors in Apache Airavata. The other type of error is caused by the users' bigWig file, called a bigWig error, which can occur when read counts are normalized, each read is mapped to a region, or read counts in minus strand are positive values. The following figures show how to identify the error [...]
<p class="description" style="padding:16px">
@@ -96,14 +96,15 @@ When users submit the experiment, the failure will be shown in the experiment su
<br>
<p class="description" style="padding:16px">
b) <b>Bigwig error</b><br>
-After the experiment is complete, no results can be downloaded and job status shows a failure (see Figure 10-S3). Users can find the dREG log file or task log file to identify the problem. Enter into <b>"storage directory"</b> by clicking the <b>"open"</b> link. The users can find <b>"ARCHIVE"</b> folder where Apache Airavata copy back all files from the computing node. Check the dREG log file (<b>out.dREG.log</b>) to see the bigwig problem or check the task log file ("slurm-tasknoxxx.ou [...]
+After the experiment is complete, no results can be downloaded and job status shows a failure (see Figure 10-S3). Users can find the dTOX log file or task log file to identify the problem. Enter into <b>"storage directory"</b> by clicking the <b>"open"</b> link. The users can find <b>"ARCHIVE"</b> folder where Apache Airavata copies back all files from the computing node. Check the dTOX log file (<b>run.dTOX.log</b>) to see the bigwig problem or check the task log file ("slurm-tasknoxxx. [...]
+tps://github.com/Danko-Lab/utils/dnase/BamToBigWig">link for DNase-I-seq</a>, or <A href="ht
+tps://github.com/Danko-Lab/utils/atacseq/BamToBigWig">link for ATAC-seq</a> to solve the problems.</p>
<div style=" display: flex;justify-content: center"><img style="align-self: center;width:70%" alt="Bigwig error" src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/failure3.png"></img></div>
<div style="clear:both;text-align:center;"><center>Figure 10-S3</center></div>
<BR>
<p>This figure shows the bigWig problems in the dREG log file.</p>
-
<div style=" display: flex;justify-content: center"><img style="align-self: center;width:70%" alt="Bigwig error(1)" src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/failure3-reason.png"></img></div>
<div style="clear:both;text-align:center;"><center>Figure 10-S4</center></div>
<BR>
@@ -125,42 +126,26 @@ After the experiment is complete, no results can be downloaded and job status sh
<div class="row">
<div class="col-sm-offset-1 col-sm-10 col-xs-12">
-<p class="description" align="justify">The input to dREG consists of two bigWig files which represent the position of RNA polymerase on the positive and negative strands. The sequence alignment and processing steps to make the input bigWig files are a major factor influencing how accurately dREG predicts TIRs. dREG makes several assumptions about data processing that are critical for success. </p>
-
-<p class="description" align="justify">Critical elements of a bioinformatics pipeline that is compatible with dREG will include:</p>
-<ul>
-<li class="description" style="align:justify"><b>Representing RNA polymerase location using a single base.</b><br/>
-<p class="description" align="justify">PRO-seq measures the location of the RNA polymerase active site, in many cases at nearly single nucleotide resolution. Therefore, it is logical to represent the coordinate of RNA polymerase using the genomic position that best represents the polymerase location, rather than representing the entire read. dREG assumes that each read is represented in the bigWig file by a single base. We have noted poor performance when reads are extended. It is critic [...]
-</li>
-
-<li class="description"><b>Include a copy of the Pol I transcription unit in the reference genome. </b><br/>
-<p class="description" align="justify">PRO-seq data resolves the location of all four RNA polymerases found in Metazoan cells (Pol I, II, III, and Mt). DNA encoding the Pol I transcription unit is highly repetitive, and is not included in most mammalian reference genomes. Nevertheless, the Pol I transcription unit is a substantial source of reads in a typical PRO-seq experiment (10-30%). Many of these reads will align spuriously to retrotransposed and non-functional copies of the Pol I t [...]
-</li>
+<p class="description" align="justify">The input to dTOX consists of two bigWig files which represent either the position of RNA polymerase on the positive and negative strands (PRO-seq) or the accessibility on the positive and negative strands (DNase-I-seq or ATAC-seq). The sequence alignment and processing steps to make the input bigWig files are a major factor influencing how accurately dTOX predicts transcription factor binding.</p>
-<li class="description"><b>Trim 3' adapters, but leave the fragments. </b><br/>
-<p class="description" align="justify">Much of the signal for dREG comes from paused RNA polymerase. RNA polymerase pauses 30-60 bp downstream of the transcription start site. Due to this short RNA fragment length, paused reads in most PRO-seq libraries will sequence a substantial amount of adapter. This leads to poor mapping rates in full-length reads. Therefore, it is crucial to remove contaminating 3' adapters so that paused fragments will map to the reference genome properly.</p>
-</li>
+<p class="description" align="justify">A key component of all datatypes is that data represents unnormalized raw counts. dTOX assumes that data represents the number of individual sequence tags that are located at each genomic position. For this reason, it is critical that input data is not normalized. The server checks to ensure that input data is expressed as integers, and will return an error if this is not the case.</p>
-<li class="description"><b>Data represents unnormalized raw counts. </b><br/>
-<p class="description" align="justify">dREG assumes that data represents the number of individual sequence tags that are located at each genomic position. For this reason, it is critical that input data is not normalized. The dREG server checks to ensure that input data is expressed as integers, and will return an error if this is not the case.</p>
-</li>
-</ul>
<p class="description"> Users can also use scripts generated in the Danko lab to create compatible bigWig files. Options for scripts at different starting points in the analysis are given below: </p>
<ul>
<li class="description"><b>Convert raw fastq files into bigWig</b>.<br/>
-<p class="description" align="justify">Our pipeline produces bigWig files that are compatible with dREG, and can be found at the following URL: <A target=_blank href="https://github.com/Danko-Lab/proseq_2.0">https://github.com/Danko-Lab/proseq_2.0</A>. Our PRO-seq pipeline takes single-end or pair-ended sequencing reads (fastq format) as input. The pipeline automates routine pre-processing and alignment steps, including pre-processing reads to remove the adapter sequences and trim based [...]
+<p class="description" align="justify">Our pipeline produces bigWig files that are compatible with dREG, and can be found at the following URLs: <A target=_blank href="https://github.com/Danko-Lab/proseq_2.0">https://github.com/Danko-Lab/proseq_2.0</A> (PRO-seq), <A target=_blank href="https://github.com/Danko-Lab/atac">https://github.com/Danko-Lab/atac</A> (ATAC-seq), <A target=_blank href="https://github.com/Danko-Lab/dnase">https://github.com/Danko-Lab/dnase</A> (DNase-I-seq). The pip [...]
</li>
<li><b>Convert mapped reads in BAM files into bigWigs</b>.<br/>
-<p class="description" align="justify">We provide a tool that converts mapped reads from a BAM file into bigWig files that are compatible with dREG. This tool is available here: <A target=_blank href="https://github.com/Danko-Lab/RunOnBamToBigWig">https://github.com/Danko-Lab/RunOnBamToBigWig</A>.</p>
+<p class="description" align="justify">We provide scripts that convert mapped reads from a BAM file into bigWig files that are compatible with dTOX. The scripts are avavailable on our GitHub page. For PRO-seq: <A target=_blank href="https://github.com/Danko-Lab/RunOnBamToBigWig">https://github.com/Danko-Lab/RunOnBamToBigWig</A>. For DNase-I-seq: <A target=_blank href="https://github.com/Danko-Lab/utils/dnase/BamToBigWig">https://github.com/Danko-Lab/utils/dnase/BamToBigWig</A>. For ATA [...]
</li>
</ul>
<p class="description">Other considerations:</p>
<ul>
-<p class="description" style="justify"> The quality and quantity of the experimental data are major factors in determining how sensitive dREG will be in detecting TREs. We have found that dREG has a reasonable statistical power for discovering TREs with as few as ~40M uniquely mappable reads, and saturates detection of TREs in well-studied ENCODE cell lines with >80M reads. To increase the number of reads available for TRE discovery, we encourage users to merge biological replicates in o [...]
+<p class="description" style="justify">The quality and quantity of the experimental data are major factors in determining how sensitive dTOX will be in detecting transcription factor binding. To increase the number of reads available for transcription factor binding detection, we encourage users to merge biological replicates in order to improve statistical power prior to running dTOX. Additionally, to compare binding predictions between conditions we recommend comparing samples at simil [...]
<p class="description" style="justify">We have found that visualizing aligned data in a genome browser prior (e.g., IGV or UCSC) to downstream analysis is a useful way to catch any data quality or alignment issues.</p>
@@ -176,7 +161,7 @@ After the experiment is complete, no results can be downloaded and job status sh
<div class="col-sm-offset-1 col-sm-10 col-xs-12">
<p class="description">
-1) dREG run generates a compressed file including the <font color="green"> dREG results </font> as follows:
+1) A dTOX run generates a compressed file including the following files:
</p>
<p class="description"> </p>
@@ -186,23 +171,9 @@ After the experiment is complete, no results can be downloaded and job status sh
<th>Description</th>
</tr>
<tr>
- <td>$PREFIX.dTOX.full.bed.gz</td>
- <td>TFBS regions with full information including chromosome, start, ending, MOTIF ID, RTFBSDB score, strand, Transcription factor, dTOX score, bound status. Decompress it with 'gunzip' in Linux.</td>
- </tr>
- <tr>
<td>$PREFIX.dTOX.bound.bed.gz</td>
- <td>TFBS regions only with bound status. Decompress it with 'gunzip' in Linux.</td>
+ <td>TFBS regions that are predicted as bound. The file includes chromosome, start, ending, MOTIF ID, RTFBSDB score, strand, dTOX score, bound status. Decompress it with 'gunzip' in Linux.</td>
</tr>
-
- <tr>
- <td>$PREFIX.dTOX.rtfbsdb.bed.gz</td>
- <td>>TFBS regions only with RTFBSDB score. Decompress it with 'gunzip' in Linux.</td>
- </tr>
-
- <tr>
- <td>$PREFIX.tar.gz</td>
- <td>Including above 5 files, can be decompressed by 'tar -xvzf' in Linux.</td>
- </tr>
</table>
<div style="padding:20px;
@@ -215,21 +186,37 @@ border-color: #dadada;" data-expandable-box-container="true">
<div class="suppress-bottom-margin add-top-margin">
<p><b>Informative position:</b>
-Loci denoted as "informative positions" meet the following criteria: contain more than 3 reads in 100 bp interval on either strand, or more than 1 read in 1Kbp interval on both strands. Informative positions are used to predict the dREG scores for TRE (Transcription Regulatory Element) identification. </p>
+Loci denoted as "informative positions" meet the following criteria: contain more than 1 reads in 400 bp interval on either strand. Informative positions are used to predict transcription factor binding. </p>
-<p><b>dTOX score:</b>
-Training and prediction is done using a Support Vector Regression model where a label of 1 indicates RNA polymerase II initialization or transciption through the informative position. The predicted values from the pre-trained model are called dREG scores. A dREG score close to 1 indicates that a position likely a TRE.
+<p><b>dTOX decision value:</b>
+Training and prediction is done using a Support Vector Regression model where a label of 1 indicates transcription factor binding. The predicted values from the pre-trained model are called dTOX decision values. A dTOX decision value close to 1 indicates that a position likely to be bound.
</p>
+</div></div>
-<p><b>RTFBSDB score:</b>
-We test 5 dREG scores around each candidate peak center using the NULL hypothesis that each point within this peak is drawn from the non-TRE distribution. This test estimates the statistical confidence of each candidate dREG peak. In the final result, FDR is applied to do multiple correction and only the peaks with adjusted p-value < 0.05 are reported.
-</p>
+<br/>
+<div style="padding:20px;
+border-style: solid;
+border-width: 5;
+border-color: #dadada;" data-expandable-box-container="true">
+<figcaption>
+<div style="padding-bottom:15px" id="Sec2">Box 2:<b> Extracting bound motifs for a specific transcription factor. </b></div>
+</figcaption>
+
+<div class="suppress-bottom-margin add-top-margin">
+<p>The dTOX output file contains the binding status of our entire set of motifs with PWMs. To find the binding status of the motifs you are interested in, you can run our R script that extracts the Motif IDs that belong to a particular transcription factor. The script is located <A target=_blank href="https://github.com/Danko-Lab/dTOX/blob/master/extract_TF.bsh">here.</A> This script requires 3 arguments: the name of the file with the dTOX results, the transcription factor you want to ex [...]
+<br/>
+<br/>
+R --vanilla --slave --args out.dTOX.bound.bed.gz TF outputFile.bed.gz < extract-bound-TF.R
+</p>
</div></div>
<br/>
+
+
+
<p class="description">
2) In the Web storage folder there are <font color="green">some files required by the WashU</font> genome browser:
</p>
@@ -240,7 +227,7 @@ We test 5 dREG scores around each candidate peak center using the NULL hypothesi
<tr>
<tr>
<td>$PREFIX.dTOX.bound.bw</td>
- <td>The bigWig file converted from the significant peaks (FDR < 0.05) with dREG scores ($PREFIX.dREG.peak.score.bed.gz).</td>
+ <td>The bigWig file converted from bound motifs ($PREFIX.dTOX.bound.bed.gz).</td>
</tr>
<tr>
<td>*.bed.gz.tbi</td>
@@ -249,19 +236,14 @@ We test 5 dREG scores around each candidate peak center using the NULL hypothesi
</table>
<p class="description">
-3) There are <font color="green">two log files </font> in the Web storage folder:</p>
+3) There are <font color="green">one log file </font> in the Web storage folder:</p>
<p class="description"> </p>
<table class="table">
<tr>
<th>File name</th> <th>Description</th> </tr>
<tr>
- <td>$PREFIX.dTOX.log</td>
- <td>Print the summary information after peak calling. If the bigWigs don't meet the requirements of dREG, the warning information will be outputted in this file.
- </td>
- </tr>
- <tr>
<td>slurm-??????.out</td>
- <td>The verbose logging output of dREG package.</td>
+ <td>The verbose log output of dTOX package.</td>
</tr>
</table>
</div>
@@ -275,10 +257,10 @@ We test 5 dREG scores around each candidate peak center using the NULL hypothesi
<div class="row">
<div class="col-sm-offset-1 col-sm-10 col-xs-12">
-<p>dREG Gateway is online service that supports Web-based science through the execution of online computational experiments and the management of data. The items below are trying to answer qustions from the users</p>
+<p>dREG Gateway is online service that supports Web-based science through the execution of online computational experiments and the management of data. Below are frequent questions about the dREG Gateway and the dTOX program.</p>
-<p><b>Q: How should I prepare bigWig files for use with the dREG gateway?</b></p>
-<p>A: Information about how to prepare files can be found <A href="https://github.com/Danko-Lab/proseq2.0"> here </A>.</p>
+<p><b>Q: How should I prepare bigWig files for use with dTOX?</b></p>
+<p>A: Information about how to prepare files can be found on the Danko lab github page here for<A href="https://github.com/Danko-Lab/proseq2.0"> PRO-seq </A>, <A href="https://github.com/Danko-Lab/utils/tree/master/dnase"> DNase </A>, and <A href="https://github.com/Danko-Lab/utils/tree/master/atacseq"> ATAC-seq </A>.</p>
<p><b>Q: How should I do when I meet the computational failure in the dREG gateway?</b></p>
<p>A: There are two types of error you may have, we explain how to identify your error and how to handle it <A href="https://dreg.dnasequence.org/pages/doc#failure"> here</A>.</p>
@@ -288,15 +270,12 @@ We test 5 dREG scores around each candidate peak center using the NULL hypothesi
<p><b>Q: What should the Safari users be aware of?</b></p>
-<p>A: By default, Safari unzips a zip file automatically when you download it. However dREG results are compressed by the 'bgzip' command which is not compatiable with the Safari method. It would be probelmatic when you download dREG results. Please refer to <A href="https://octet.oberlin.edu/does-your-mac-unzip-zip-files-automatically/"> this link </A> to disable this feature in Safari and then download the compressed results from dREG gateway. </br>
+<p>A: By default, Safari unzips a zip file automatically when you download it. However dTOX results are compressed by the 'bgzip' command which is not compatiable with the Safari method. It would be problematic when you download dTOX results. Please refer to <A href="https://octet.oberlin.edu/does-your-mac-unzip-zip-files-automatically/"> this link </A> to disable this feature in Safari and then download the compressed results from dREG gateway. </br>
Secondly, when you click the genome browser link, please use the Left-Click, don't use Right-Click menu and the menu option "open a new tab".
</p>
-<p><b>Q: What types of enhancers and promoters can be identified using the dREG gateway?</b></p>
-<p>A: As a general rule of thumb, high-quality datasets provide very similar groups of enhancers and promoters as ChIP-seq for H3K27ac. This suggests that dREG identifies the location of all of the so-called 'active' class of enhancers and promoters. </p>
-
-<p><b>Q: Will the dREG gateway work with my data type?</b></p>
-<p>A: The dREG gateway will work well with data collected by any run-on and sequencing method, including GRO-seq, PRO-seq, or ChRO-seq. Other methods that map the location of RNA polymerase genome wide using alternative tools (for example, NET-seq) will most likely work well, but are not officially supported.</p>
+<p><b>Q: Will dTOX work with my data type?</b></p>
+<p>A: dTOX was trained and tested on PRO-seq, ATAC-seq, and DNase-I-seq. dTOX will also work well with data collected by any run-on and sequencing method, including GRO-seq, PRO-seq, or ChRO-seq. Other methods that map the location of RNA polymerase genome wide using alternative tools (for example, NET-seq) will most likely work well, but are not officially supported.</p>
<p><b>Q: Will the pre-trained models work using data from my species?</b></p>
<p>A: Models are currently available only in mammalian organisms. The length and density of genes, which vary considerably between highly divergent species, affects the way that a transcribed promoter or enhancer looks. For this reason, models can only be used in species. We are working to create models in widely-used model organisms, including drosophila and C. elegans. </p>
@@ -307,13 +286,10 @@ Secondly, when you click the genome browser link, please use the Left-Click, don
<p><b>Q: How long do my data and results keep in the dREG gateway?</b></p>
<p>A: One month.</p>
-<p><b>Q: How to I cite the dREG gateway?</b></p>
-<p>A: Please cite one of our papers if you use dREG results in your publication:<BR/>
-<A target="_blank" href="http://www.nature.com/nmeth/journal/v12/n5/full/nmeth.3329.html">
-(1) Danko, C. G., Hyland, S. L., Core, L. J., Martins, A. L., Waters, C. T., Lee, H. W., ... & Siepel, A. (2015). Identification of active transcriptional regulatory elements from GRO-seq data. Nature methods, 12(5), 433-438. </A></p>
+<p><b>Q: How do I cite dTOX?</b></p>
+<p>A: Please cite our papers if you use dTOX results in your publication:<BR/>
<A target="_blank" href="https://www.biorxiv.org/content/early/2018/05/14/321539.abstract">
-(2) Wang, Z., Chu, T., Choate, L. A., & Danko, C. G. (2018). Identification of regulatory elements from nascent transcription using dREG. bioRxiv, 321539. </A></P>
-
+(1) ADD CITATION. Choate, L. A., Wang, Z., & Danko, C. G. (2018). Identification of transcription factor binding using genome-wide accessibility and transcription. bioRxiv. </A></P>
<p><b>Q: Do I have to create account before using this service?</b></p>
<p>A: Yes, this system is supported by an NSF funded supercomputing resource known as <A title="XSEDE" href="http://www.xsede.org">XSEDE</A>, who regularly needs to report bulk usage statistics to NSF. Nevertheless, data that you provide are completely safe.</p>
diff --git a/public/themes/dreg/partials/header.blade.php b/public/themes/dreg/partials/header.blade.php
index a470341..e532620 100755
--- a/public/themes/dreg/partials/header.blade.php
+++ b/public/themes/dreg/partials/header.blade.php
@@ -1,4 +1,8 @@
<title>dREG Gateway</title>
+<link rel="icon"
+ type="image/png"
+ href="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/dregicon.png">
+
<div id="navbar" class="navbar navbar-inverse">
<div class="container-fluid" style="background:white;">
<div class="navbar-header" style="background:white;">
@@ -21,7 +25,7 @@ color:blue;
<li><a class="scroll hidden" href="#home"></a></li>
<li><a class="scroll" @if( $_SERVER['REQUEST_URI'] === "/" ) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/">Home</a></li>
<li><a class="scroll" @if(strpos($_SERVER['REQUEST_URI'], "pages/doc") !== false) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/pages/doc">dREG Documentation</a></li>
- <li><a class="scroll" @if(strpos($_SERVER['REQUEST_URI'], "pages/dtox-doc") !== false) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/pages/dtox-doc">dTOX dcumentation</a></li>
+ <li><a class="scroll" @if(strpos($_SERVER['REQUEST_URI'], "pages/dtox-doc") !== false) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/pages/dtox-doc">dTOX documentation</a></li>
<li><a class="scroll" @if(strpos($_SERVER['REQUEST_URI'], "pages/software") !== false) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/pages/software">Software/Package</a></li>
<li><a class="scroll" @if(strpos($_SERVER['REQUEST_URI'], "pages/about") !== false) style="color:blue" @else style="color:black" @endif href="{{ URL::to('/') }}/pages/about">About</a></li>
diff --git a/public/themes/dreg/partials/software.blade.php b/public/themes/dreg/partials/software.blade.php
index 686983c..892e515 100755
--- a/public/themes/dreg/partials/software.blade.php
+++ b/public/themes/dreg/partials/software.blade.php
@@ -13,26 +13,32 @@ The dREG package is developed to detect the divergently oriented RNA polymerase
<p class="description">[2] <B>dREG.HD package</B>: <A href="https://github.com/Danko-Lab/dREG.HD">https://github.com/Danko-Lab/dREG.HD</A>.</p>
<p class="description">The dREG.HD pa/ckage refines the location of TREs obtained using dREG by imputing DNAse-I hypersensitivity.</p>
- <p class="description">[3] <B>Rgtsvm package</B>: <A href="https://github.com/Danko-Lab/Rgtsvm">https://github.com/Danko-Lab/Rgtsvm</A>.</p>
+
+
+ <p class="description">[3] <B>dTOX package</B>: <A href="https://github.com/Danko-Lab/dTOX">https://github.com/Danko-Lab/dTOX</A>.</p>
+ <p class="description">The dTOX package detects transcription factor binding in PRO-seq, DNase-I-seq, and ATAC-seq using support vector machines and random forests. </p>
+
+
+ <p class="description">[4] <B>Rgtsvm package</B>: <A href="https://github.com/Danko-Lab/Rgtsvm">https://github.com/Danko-Lab/Rgtsvm</A>.</p>
<p class="description">
Rgtsvm implements support vector classification and support vector regression on a GPU to accelerate the computational speed of training and predicting large-scale models. </p>
- <p class="description">[4] <B>rtfbsdb package</B>: <A href="https://github.com/Danko-Lab/rtfbs_db">https://github.com/Danko-Lab/rtfbs_db</A>.</p>
+ <p class="description">[5] <B>rtfbsdb package</B>: <A href="https://github.com/Danko-Lab/rtfbs_db">https://github.com/Danko-Lab/rtfbs_db</A>.</p>
<p class="description">
Rtfbsdb implements TFBS scaning acorss whole genome and TF enrichment test with the aid of CIS-BP, Jolma and other TF databases.
</p>
- <p class="description">[5] <B>tfTarget package</B>: <A href="https://github.com/Danko-Lab/tfTarget">https://github.com/Danko-Lab/tfTarget</A>.</p>
+ <p class="description">[6] <B>tfTarget package</B>: <A href="https://github.com/Danko-Lab/tfTarget">https://github.com/Danko-Lab/tfTarget</A>.</p>
<p class="description">
Identify transcription factor-enhancer/promoter-gene network from run-on sequencing data.
</p>
- <p class="description">[6] <B>Proseq 2.0</B>: <A href="https://github.com/Danko-Lab/proseq2.0">https://github.com/Danko-Lab/proseq2.0</A>.</p>
+ <p class="description">[7] <B>Proseq 2.0</B>: <A href="https://github.com/Danko-Lab/proseq2.0">https://github.com/Danko-Lab/proseq2.0</A>.</p>
<p class="description">
Preprocesses and Aligns Run-On Sequencing (PRO/GRO/ChRO-seq) data from Single-Read or Paired-End Illumina Sequencing.
</p>
- <p class="description">[7] <B>Airavata PHP Gateway</B>: <A href="https://github.com/apache/airavata-php-gateway.git">https://github.com/apache/airavata-php-gateway.git</A>.</p>
+ <p class="description">[8] <B>Airavata PHP Gateway</B>: <A href="https://github.com/apache/airavata-php-gateway.git">https://github.com/apache/airavata-php-gateway.git</A>.</p>
<p class="description">
Airavata PHP Gateway provides an API to build web sites which interact with high performance computers that are part of XSEDE.
</p>
diff --git a/public/themes/dreg/partials/template.blade.php b/public/themes/dreg/partials/template.blade.php
index 0110898..1325121 100755
--- a/public/themes/dreg/partials/template.blade.php
+++ b/public/themes/dreg/partials/template.blade.php
@@ -3,7 +3,7 @@
<div class="col-md-offset-2 col-md-8 breathing-space scigap-info" >
<h1 class="text-center">Welcome to dREG and dTOX gateway!</h1>
<p class="text-center" style="color:#cccccc;">
- Find the location of enhancers and promoters using PRO-seq, GRO-seq, and ChRO-seq data.<br/>
+ Find the location of transcriptional regulatory elements and transcription factoring binding using genomic data.<br/>
</p>
<p class="text-center" style="color:#444444;">
The gateway status and updates are <A target=_blank href="https://github.com/Danko-Lab/dREG/blob/master/gateway-update.md"><B>here!</b></A>
@@ -13,7 +13,7 @@
<div class="col-md-offset-1 col-md-5" style="margin-left: 5%" >
<H2> How is dREG used?</H2>
<p style="font-size:14px; margin-top:10px; text-align:justify">
- The dREG model in the gateway predicts the location of enhancers and promoters using PRO-seq, GRO-seq, or ChRO-seq data. The server takes as input bigWig files provided by the user, which represent PRO-seq signal on the plus and minus strand. The gateway uses pre-trained dREG model to identify divergent transcript start sites and impute the predicted DNase-1 hypersensitivity signal across the genome. The current dREG model works in any mammalian organism.</p>
+ The dREG model in the gateway predicts the location of enhancers and promoters using PRO-seq, GRO-seq, or ChRO-seq data. The server takes as input bigWig files provided by the user, which represent PRO-seq signal on the plus and minus strand. The gateway uses a pre-trained dREG model to identify divergent transcript start sites and impute the predicted DNase-I hypersensitivity signal across the genome. The current dREG model works in any mammalian organism.</p>
<p style="font-size:14px; margin-top:10px;text-align:justify">
Registered users need only upload experimental data in the required format and push the start button. Once the job is finished, the user will be notified by e-mail. Results can be downloaded to the user’s local machine, or viewed in the Genome Browser via the handy trackhub link. </p>
@@ -38,11 +38,17 @@ Registered users need only upload experimental data in the required format and p
<div class="col-md-offset-1 col-md-5" style="margin-left: 5%">
<H2> How is dTOX used? </H2>
- <p color="red">Under construction, please ignore this section! </p>
<p style="font-size:14px; margin-top:10px;text-align:justify">
-The dTOX models in the gateway predict the binding status of transcription factor binding sites using PRO-seq, ATAC-seq, or DNase-1-seq data. The server takes as input bigWig files provided by the user, which represent the PRO-seq, ATAC-seq, or DNase-1-seq signal on the plus and minus strand. Once the user selects the transcription factors to predict on, the gateway uses a pre-trained dTOX model to identify transcription factor binding patterns. The current dTOX models work in any mammal [...]
+The dTOX models in the gateway predict the binding status of transcription factor binding sites using PRO-seq, ATAC-seq, or DNase-I-seq data. The server takes as input bigWig files provided by the user, which represent the PRO-seq, ATAC-seq, or DNase-1-seq signal on the plus and minus strand. The gateway uses two pre-trained dTOX models to identify transcription factor binding patterns genome-wide. The current dTOX models work in any mammalian organism and on any motif that has an associ [...]
<p style="font-size:14px; margin-top:10px;text-align:justify">
The web operations are same as the dREG model. Users need to login -> upload data -> run data. Results can be downloaded or viewed in the WashU Genome browser.</p>
+ <p style="font-size:14px; margin-top:5px;text-align:justify">
+ <img src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/webdev-bullet-icon.png" style="height:20px"></img>
+ Use the Danko lab's pipeline to <b>convert BAM files</b> of mapped reads to bigWig (<A ta
+rget=_blank href="https://github.com/Danko-Lab/RunOnBamToBigWig">here for PRO-seq</A>), (<A ta
+rget=_blank href="https://github.com/Danko-Lab/utils/dnase/BamToBigWig">here for DNase-I-seq</A>), and (<A ta
+rget=_blank href="https://github.com/Danko-Lab/utils/atacseq/BamToBigWig">here for ATAC-seq</A>).
+ </p>
<p style="font-size:14px; margin-top:5px;text-align:justify">
<img src="{{ URL::to('/') }}/themes/{{Session::get('theme')}}/assets/img/webdev-bullet-icon.png" style="height:20px"></img>