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DolphinSuite
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<p>All raw sequencing data (scRNA-Seq, scATAC-Seq and CAGE-Seq) were
processed by pipelines developed within the interactive pipeline manager
<a href="./dolphinsuite.html">DolphinNext</a> (<a
href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6714-x">Yukselen
et. al 2020</a>). The metadata as well as the processed datasets are
currently being hosted in <a
href="./dolphinsuite.html">DolphinSuite</a>, an end-to-end
bioinformatics analysis platform.</p>
<div id="dolphinsuite-platforms" class="section level2">
<h2>DolphinSuite Platforms</h2>
<p><a href="https://www.umassmed.edu/biocore/" target="_blank">UMass
Chan Medical School BioCore</a> has developed
<strong>DolphinSuite</strong>, a bioinformatics platform to support the
analysis of high throughput data. DolphinSuite tracks samples from
sample collection to data processing (sequencing, proteomics,
metabolomics) and provides interactive analysis using an intuitive web
interface. DolphinSuite is built to ensure secure access to the
processed data using 3rd party applications for tailor-made analysis and
data sharing.</p>
<p>DolphinSuite is comprised of three major components that supports
distinct aspects of high throughput data analysis.</p>
<table>
<tbody>
<tr>
<td style="text-align:center;width:33%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com" target="_blank" style="font-size: 1.5em;">DolphinNext
(Dnext)</a>
</p>
<img width="300" height="220" src="images/dolphinnext.png" class="center">
<br>
<p>
<strong>Dnext</strong>: a distributed data processing platform for high
throughput genomics
</p>
</td>
<td style="text-align:center;width:33%; vertical-align: text-top;">
<p>
<a href="https://dmeta.dolphinnext.com" target="_blank" style="font-size: 1.5em;">DolphinMeta
(Dmeta)</a>
</p>
<img width="300" height="200" src="images/dmeta.png" class="center">
<br>
<p>
<strong>Dmeta</strong>: automated data processing and management using
ontology-based metadata tracking system
</p>
</td>
<td style="text-align:center; width:33%; vertical-align: text-top;">
<p>
<a href="https://dportal.dolphinnext.com" target="_blank" style="font-size: 1.5em;">DolphinPortal
(Dportal)</a>
</p>
<img width="300" height="200" src="images/dportal.png" class="center">
<br>
<p>
<strong>Dportal</strong>: a user-friendly and interactive data browser
for filtering and querying
</p>
</td>
</tr>
</tbody>
</table>
<p><br> <br></p>
</div>
<div id="preprocessing-pipelines" class="section level2">
<h2>Preprocessing Pipelines</h2>
<p>DolphinNext is a revolutionary pipeline management system that allows
users to <strong>interactively customize data pre-processing</strong>
workflows and ensures <strong>reproducibility</strong> of analysis
results. Below, we give a summary of three pipelines that are used to
process scRNA-Seq, scATAC-Seq and CAGE-Seq reads incorporated in this
project.</p>
<table>
<tbody>
<tr>
<td style="text-align:center;width:40%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=12" target="_blank" style="font-size: 1.2em;">scRNA-Seq
(Tasic et. al 2018) Pipeline</a>
</p>
<img width="400" height="240" src="images/scRNA-Seq%20pipeline.png" class="center">
<br>
</td>
<td style="width:60%; vertical-align: text-top; padding: 10px">
<p>
The <strong>scRNA-Seq (Tasic et. al 2018) pipeline</strong> includes
Quality Control, rRNA filtering, Genome Alignment using STAR and
estimates gene expression levels by GenomeAlignment Package in R.
</p>
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
For Quality Control, we use FastQC to create qc outputs. There are
optional read quality filtering (trimmomatic), read quality trimming
(trimmomatic), adapter removal (cutadapt) processes available.
</li>
<li>
STAR is used to count or filter out common RNAs (eg. rRNA, miRNA, tRNA,
piRNA etc.).
</li>
<li>
STAR is used to align RNA-Seq reads to a genome.
</li>
<li>
SummarizeOverlaps is used to calculate gene counts.
</li>
</ol>
<p style="margin : 0; padding-top:0;">
<strong>Docker</strong>:
<a href="https://hub.docker.com/r/dolphinnext/tasic2018_scrnaseq_pipeline" target="_blank">https://hub.docker.com/r/dolphinnext/tasic2018_scrnaseq_pipeline</a>
</p>
<p>
<strong>GitHub</strong>:
<a href="https://github.com/dolphinnext/tasic2018_scrnaseq_pipeline" target="_blank">https://github.com/dolphinnext/tasic2018_scrnaseq_pipeline</a>
</li>
</p>
</td>
</tr>
<tr>
<td style="text-align:center;width:40%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=18" target="_blank" style="font-size: 1.2em;">scATAC-Seq
(Graybuck et. al 2021) Pipeline</a>
</p>
<img width="400" height="180" src="images/scATAC-Seq%20pipeline.png" class="center">
<br>
</td>
<td style="width:60%; vertical-align: text-top; padding: 10px">
<p>
The <strong>scATAC-Seq (Graybuck et. al 2021) pipeline</strong> includes
a set of tools necessary for pre-processing ATAC-Seq libraries prepared
as in (Graybuck et. al 2021).
</p>
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
Trim Galore tool is used to remove adapters from reads.
</li>
<li>
Trimmed and untrimmed reads are aligned to the reference using Bowtie.
</li>
<li>
Duplicates reads are deleted using Samtools.
</li>
</ol>
<p style="margin : 0; padding-top:0;">
<strong>Docker</strong>:
<a href="https://hub.docker.com/r/dolphinnext/graybuck2021_scatacseq_pipeline " target="_blank">https://hub.docker.com/r/dolphinnext/graybuck2021_scatacseq_pipeline
</a>
</p>
<p>
<strong>GitHub</strong>:
<a href="https://github.com/dolphinnext/graybuck2021_scatacseq_pipeline " target="_blank">https://github.com/dolphinnext/graybuck2021_scatacseq_pipeline
</a>
</li>
</p>
</td>
</tr>
<tr>
<td style="text-align:center;width:40%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=38" target="_blank" style="font-size: 1.2em;">scATAC-Seq
(Mich et. al 2021) Pipeline</a>
</p>
<img width="400" height="180" src="images/mich%20pipeline.png" class="center">
<br>
</td>
<td style="width:60%; vertical-align: text-top; padding: 10px">
<p>
The <strong>scATAC-Seq (Mich et. al 2021) pipeline</strong> includes a
set of tools necessary for pre-processing ATAC-Seq libraries prepared as
in (Mich et. al 2021).
</p>
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
Reads are aligned to the reference using Bowtie2.
</li>
<li>
Low quality, secondary and unmapped reads are deleted using Samtools.
</li>
</ol>
<p style="margin : 0; padding-top:0;">
<strong>Docker</strong>:
<a href="https://hub.docker.com/r/dolphinnext/mich2021_scatacseq_pipeline " target="_blank">https://hub.docker.com/r/dolphinnext/mich2021_scatacseq_pipeline
</a>
</p>
<p>
<strong>GitHub</strong>:
<a href="https://github.com/dolphinnext/mich2021_scatacseq_pipeline " target="_blank">https://github.com/dolphinnext/mich2021_scatacseq_pipeline
</a>
</li>
</p>
</td>
</tr>
<tr>
<td style="text-align:center;width:40%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=21" target="_blank" style="font-size: 1.2em;">CAGE-Seq
Pipeline</a>
</p>
<img width="400" height="160" src="images/CAGE-Seq%20pipeline.png" class="center">
<br>
</td>
<td style="width:60%; vertical-align: text-top; padding: 10px">
<p>
The <strong>CAGE-seq pipeline</strong> includes rRNA filtering, Genome
Alignment using STAR, and peak calling using MACS2.
</p>
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
STAR is used to count or filter out common RNAs (eg. rRNA, miRNA, tRNA,
piRNA etc.).
</li>
<li>
STAR is used to align RNA-Seq reads to a genome.
</li>
<li>
MACS2 is used for calling peaks in aligned bam files.
</li>
</ol>
<p style="margin : 0; padding-top:0;">
<strong>Docker</strong>:
<a href="https://hub.docker.com/r/dolphinnext/cageseq_pipeline" target="_blank">https://hub.docker.com/r/dolphinnext/cageseq_pipeline</a>
</p>
<p>
<strong>GitHub</strong>:
<a href="https://github.com/dolphinnext/cageseq_pipeline" target="_blank">https://github.com/dolphinnext/cageseq_pipeline</a>
</li>
</p>
</td>
</tr>
</tbody>
</table>
<p><br></p>
</div>
<div id="downstream-analysis-pipelines" class="section level2">
<h2>Downstream Analysis Pipelines</h2>
<p>DolphinNext can also be used to design downstream analysis pipelines
that may incorporate processed sequencing datasets to further
investigate cell types of interests and build necessary files for online
applications such as <a href="./cellxgenebrowser.html">Cellxgene</a> and
<a href="./ucscbrowser.html">UCSC Track Hub</a>.</p>
<p>All <strong>Aggregate Analysis</strong> pipelines incorporate a few
number of common processes as well as steps geared towards each
individual sequencing technology or dataset.</p>
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
Aggregating Bam Files with unique mapped reads to Cell Types.
</li>
<li>
Peak Calling with MACS2.
</li>
<li>
Creating BigWig files for UCSC Genome Browser.
</li>
<li>
Creating auxiliary files for building custom UCSC track hubs.
</li>
<li>
Single cell RNA downstream analysis using Seurat (only for scRNA-Seq
pipeline)
</li>
<li>
Making h5ad files for visualization in Cellxgene (only for scRNA-Seq
pipeline)
</li>
</ol>
<p>We have designed an additional downstream analysis pipeline (see
<strong>Integrate-MultiOmics-Tracks</strong>) to build a large custom
UCSC Track Hub of combined scRNA-Seq, scATAC-Seq and CAGE-Seq analysis.
The resulting UCSC track hub can be accessed from here: <a
href="./ucscbrowser_mouse.html">mouse</a> and <a
href="./ucscbrowser_human.html">human</a>.</p>
<br>
<table>
<tbody>
<tr>
<td style="text-align:center;width:33%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=20" target="_blank" style="font-size: 1.2em;">Aggregate
Analysis (Tasic 2018)</a>
</p>
<img width="300" height="180" src="images/aggregate%20Tasic.png" class="center">
</td>
<td style="text-align:center; width:33%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=19" target="_blank" style="font-size: 1.2em;">scATAC-Seq
Aggregate Analysis</a>
</p>
<img width="300" height="180" src="images/aggregate%20Graybuck.png" class="center">
</td>
<td style="text-align:center;width:33%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=22" target="_blank" style="font-size: 1.2em;">Cage-Seq
Aggregate Analysis</a>
</p>
<img width="300" height="130" src="images/aggregate%20CAGE-Seq.png" class="center">
</td>
</tr>
<tr>
<td style="text-align:center;width:33%; vertical-align: text-top;">
<p>
<a href="https://dnext.dolphinnext.com/index.php?np=1&id=23" target="_blank" style="font-size: 1.2em;">Integrate-MultiOmics-Tracks</a>
</p>
<img width="300" height="280" src="images/multi-omics%20pipeline.png" class="center">
<br>
</td>
<td colspan="2" style="width:66%; vertical-align: text-top; padding: 10px">
<p>
The <strong>Integrate-MultiOmics-Tracks</strong> pipeline generates a
custom <strong>USCS Track Hub</strong> and auxiliary tables for
interrogating RNA, ATAC and CAGE seq reads from following studies:
</p>
<!-- <ol> -->
<!-- <li>ATAC-seq (Graybuck et. al 2021): Enhancer viruses for combinatorial cell-subclass- specific labeling.</li> -->
<!-- <li>RNA-seq (Tasic et. al 2018): Shared and distinct transcriptomic cell types across neocortical areas.</li> -->
<!-- <li>CAGE-seq: FANTOM5 CAGE profiles of human and mouse samples.</li> -->
<!-- </ol> -->
<p>
<strong>Steps</strong>:
</p>
<ol>
<li>
Collect bigWig files from multiple DolphinNext runs.
</li>
<li>
Build a custom UCSC track hub for all tracks of scRNA-Seq, scATAC-Seq
and CAGE-Seq reads
</li>
<li>
Aggregate counts from scRNA-seq data for each cell type.
</li>
</ol>
</td>
</tr>
</tbody>
</table>
<p><br></p>
</div>
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