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Missing help #153

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885f7ae
added bs_pe_4a.html
Apr 7, 2020
0af9ae3
added bs_pe_5a.html
Apr 7, 2020
28c4f0f
added missing tools in the header
Apr 7, 2020
99c2128
added missing tools in the description section
Apr 7, 2020
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67 changes: 67 additions & 0 deletions bs_pe_4a.html
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<!DOCTYPE html>
<html lang="en">
<style>
table {
color: #ED1D99;
}
h4 {
color: #345CB3;
}
p {
color: #345CB3;
border:2px;
border-radius: 5px;
border-style:solid;
border-color:#ED1D99;
padding: 1em;
}
div {
text-indent:10px;
}
</style>
<head>
<meta charset="UTF-8">
<title>Bismark</title>
</head>
<body>
<h4>Bismark</h4>
<FONT SIZE="2">
<!--
<h4><img src="./logo_destair.png" height="15" /> Tool Rating:</h4>
<div>
<table>
<tr>
<td>Ease of use:</td>
<td>&#10026;&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>User base:</td>
<td>&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>Sensitivity:</td>
<td>-</td>
</tr>
<tr>
<td>Speed:</td>
<td>&#10026;&#10026;&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>Configurability:</td>
<td>&#10026;&#10026;&#10026;&#10026;</td>
</tr>
</table>
</div>
-->
<h4>Description:</h4>
<p>
<b>Bismark</b> analyses BS-Seq data by performing both read mapping and
methylation calling in a single run. Its output distinguishes between cytosines
in CpG, CHG and CHH contexts, and enables the visualization and interpretation
of the provided methylated data.
</p>
<h4>Reference:</h4>
<a target="_blank" href="https://doi.org/10.1093/bioinformatics/btr167">Bismark</a>
</FONT>
</body>
</html>
84 changes: 84 additions & 0 deletions bs_pe_5a.html
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<!DOCTYPE html>
<html lang="en">
<style>
table {
color: #ED1D99;
}
h4 {
color: #345CB3;
}
p {
color: #345CB3;
border:2px;
border-radius: 5px;
border-style:solid;
border-color:#ED1D99;
padding: 1em;
}
div {
text-indent:10px;
}
</style>
<head>
<meta charset="UTF-8">
<title>Samtools, MethylDackel, Bedtools, Join and AWK</title>
</head>
<body>
<h4>Samtools, MethylDackel, Bedtools, Join and AWK</h4>
<FONT SIZE="2">
<!--
<h4><img src="./logo_destair.png" height="15" /> Tool Rating:</h4>
<div>
<table>
<tr>
<td>Ease of use:</td>
<td>&#10026;&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>User base:</td>
<td>&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>Sensitivity:</td>
<td>-</td>
</tr>
<tr>
<td>Speed:</td>
<td>&#10026;&#10026;&#10026;&#10026;&#10026;</td>
</tr>
<tr>
<td>Configurability:</td>
<td>&#10026;&#10026;&#10026;&#10026;</td>
</tr>
</table>
</div>
-->
<h4>Description:</h4>
<p>
<b>Samtools</b> is a library of utilities for post-processing alignments in the
SAM format, <i>e.g.</i> indexing, variant calling and alignment viewing.<br>
<br>
<b>MethylDackel</b> processes coordinate-sorted and indexed BAM/CRAM files that
contain BS-Seq alignments, and extracts per-base methylation metrics.
MethylDackel also requires an indexed reference genome in the FASTA format.<br>
<br>
<b>Bedtools</b> is a library of utilities for genomic analysis, <i>e.g.</i>
merge, count, complement and shuffle genomic intervals from multiple files in
different file formats, such as BAM, BED, GFF/GTF, VCF.<br>
<br>
<b>Join</b> is a Galaxy utility which is used to join two files that share a
column of values. While this operation can be performed using other tools, <i>
e.g.</i> AWK, this tool provides a convenient graphical user interface, which
makes it easy to use and parameterize.<br>
<br>
<b>AWK</b> is a programming language that can be used script operations such as
parsing, editing, and extract table column values.
</p>
<h4>Reference:</h4>
<a target="_blank" href="https://doi.org/10.1093/bioinformatics/btp352">Samtools</a>
<a target="_blank" href="https://github.com/dpryan79/MethylDackel">MethylDackel</a>
<a target="_blank" href="https://doi.org/10.1093/bioinformatics/btq033">Bedtools</a>
<a target="_blank" href="https://www.gnu.org/software/gawk/manual/gawk.html">AWK</a>
</FONT>
</body>
</html>
15 changes: 11 additions & 4 deletions bs_pe_5a.yaml
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Expand Up @@ -5,10 +5,17 @@ title_default: 'BS-Seq analysis (paired-end reads)'
steps:
- title: '<b>Outline</b>'
element: '#masthead:visible'
content: 'In this tour we will infer genome-wide methylation rates in a CpG context.<br>
Here, we will leverage on two tools:<br>
- <b>Samtools</b>, to extract uniquely mapped and properly paired sequences from aligned input data and mark duplicons<br>
- <b>MethylDackel</b> to quantify the methylated reads of the provided CpG context file.'
content: 'In this tour we will infer genome-wide methylation rates in a CpG
context.<br>
Here, we will leverage on:<br>
- <b>Samtools</b>, to extract uniquely mapped and properly paired sequences
from aligned input data and mark duplicons<br>
- <b>MethylDackel</b>, to quantify the methylated reads of the provided CpG
context file.<br>
- <b>Bedtools</b>, to extract the CpG methylation of potential promoters and
calculate mean methylation levels<br>
- <b>Join</b>, to join files on a shared column of values<br>
- <b>AWK</b>, to parse and extract table columns depending on their values.'
placement: bottom


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