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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/39269?offset=470</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</guid>
	<pubDate>Thu, 02 Aug 2018 07:39:46 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37473/lsc-a-long-read-error-correction-tool</link>
	<title><![CDATA[LSC :a long read error correction tool]]></title>
	<description><![CDATA[<h2>Getting Started</h2>
<p>These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.</p>
<ul>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_requirements.asp">LSC_requirements</a>&nbsp;for running LSC.</li>
<li><a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_download.asp">Download</a>&nbsp;and set-up the LSC package.</li>
<li>Follow the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_tutorial.asp">tutorial</a>&nbsp;to see how LSC works on some example data.</li>
<li>Read the&nbsp;<a href="https://www.healthcare.uiowa.edu/labs/au/LSC/LSC_manual.asp">manual</a>&nbsp;if anything is unclear.</li>
<li>You're ready, Happy LSCing!</li>
</ul>
<h2>Latest publication</h2>
<p><span>Kin Fai Au, Jason Underwood, Lawrence Lee and Wing Hung Wong&nbsp;</span><br><strong>Improving PacBio Long Read Accuracy by Short Read Alignment&nbsp;</strong><span>[</span><a href="http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0046679">Manuscript</a><span>]&nbsp;</span><br><em>PLoS ONE</em><span>&nbsp;2012. 7(10): e46679. doi:10.1371/journal.pone.0046679</span></p><p>Address of the bookmark: <a href="https://www.healthcare.uiowa.edu/labs/au/LSC/" rel="nofollow">https://www.healthcare.uiowa.edu/labs/au/LSC/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40212/kalign-fast-multiple-sequence-alignment-program-for-biological-sequences</guid>
	<pubDate>Fri, 01 Nov 2019 00:20:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40212/kalign-fast-multiple-sequence-alignment-program-for-biological-sequences</link>
	<title><![CDATA[Kalign: fast multiple sequence alignment program for biological sequences.]]></title>
	<description><![CDATA[<p><span>Kalign is a fast multiple sequence alignment program for biological sequences.</span></p>
<p>Align sequences and output the alignment in MSF format:</p>
<pre><code>kalign -i BB11001.tfa -f msf  -o out.msf
</code></pre>
<p>Align sequences and output the alignment in clustal format:</p>
<pre><code>kalign -i BB11001.tfa -f clu -o out.clu
</code></pre>
<p>Re-align sequences in an existing alignment:</p>
<pre><code>kalign -i BB11001.msf  -o out.afa
</code></pre>
<p>Reformat existing alignment:</p>
<pre><code>kalign -i BB11001.msf -r afa -o out.afa</code></pre><p>Address of the bookmark: <a href="https://github.com/TimoLassmann/kalign" rel="nofollow">https://github.com/TimoLassmann/kalign</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</guid>
	<pubDate>Thu, 09 Jul 2020 03:13:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41959/rna-bloom-a-fast-and-memory-efficient-de-novo-transcript-sequence-assembler</link>
	<title><![CDATA[RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler]]></title>
	<description><![CDATA[<p><strong>RNA-Bloom</strong><span>&nbsp;</span>is a fast and memory-efficient<span>&nbsp;</span><em>de novo</em><span>&nbsp;</span>transcript sequence assembler. It is designed for the following sequencing data types:</p>
<ul>
<li>single-end/paired-end bulk RNA-seq (strand-specific/agnostic)</li>
<li>paired-end single-cell RNA-seq (strand-specific/agnostic)</li>
<li>nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)</li>
</ul>
<p>Written by<span>&nbsp;</span><a>Ka Ming Nip</a><span>&nbsp;</span>✉️</p><p>Address of the bookmark: <a href="https://github.com/bcgsc/RNA-Bloom" rel="nofollow">https://github.com/bcgsc/RNA-Bloom</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43639/fastv-detect-virus</guid>
	<pubDate>Sat, 11 Dec 2021 08:04:10 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43639/fastv-detect-virus</link>
	<title><![CDATA[fastv - detect virus]]></title>
	<description><![CDATA[<p><span>fastv is an ultra-fast tool for identification of SARS-CoV-2 and other microbes from sequencing data. It detects microbial sequences from FASTQ data, generates JSON reports and visualizes the result in HTML reports. This tool can be used to detect viral infectious diseases, like COVID-19. This tool supports both short reads (Illumina, BGI, etc.) and long reads (ONT, PacBio, etc.)</span></p><p>Address of the bookmark: <a href="https://github.com/OpenGene/fastv" rel="nofollow">https://github.com/OpenGene/fastv</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44641/heliano-a-fast-and-accurate-tool-for-detection-of-helitron-like-elements</guid>
	<pubDate>Tue, 13 Aug 2024 07:16:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44641/heliano-a-fast-and-accurate-tool-for-detection-of-helitron-like-elements</link>
	<title><![CDATA[HELIANO: A fast and accurate tool for detection of Helitron-like elements]]></title>
	<description><![CDATA[<p><span>Helitron-like elements (HLE1 and HLE2) are DNA transposons. They have been found in diverse species and seem to play significant roles in the evolution of host genomes. Although known for over twenty years, Helitron sequences are still challenging to identify. Here, we propose HELIANO (Helitron-like elements annotator) as an efficient solution for detecting Helitron-like elements.</span></p>
<p>https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae679/7730539?login=true</p><p>Address of the bookmark: <a href="https://github.com/Zhenlisme/heliano/" rel="nofollow">https://github.com/Zhenlisme/heliano/</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</guid>
	<pubDate>Thu, 05 Sep 2013 07:24:02 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/4288/new-born-babies-get-ready-to-know-their-whole-genome-soon</link>
	<title><![CDATA[New born babies get ready to know their whole genome soon!!!]]></title>
	<description><![CDATA[<p>USA launch a pilot projects to examine medical information of newborn baby, which are being funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Human Genome Research Institute (NHGRI), both parts of the National Institutes of Health.</p><p>Awards of $5 million to four grantees have been made in fiscal year 2013 under the Genomic Sequencing and Newborn Screening Disorders research program. The program will be funded at $25 million over five years, as funds are made available.</p><p>"Hundreds of US babies will be pioneers in genomic medicine through a&nbsp;US$25-million programme to sequence their genomes&nbsp;soon after they are born."</p><p><strong>Source</strong>:</p><p><a href="http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html">http://blogs.nature.com/news/2013/09/scientists-to-sequence-hundreds-of-newborns-genomes.html</a></p><p><a href="http://www.genome.gov/27554919">http://www.genome.gov/27554919</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</guid>
	<pubDate>Wed, 26 Jul 2017 07:49:29 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33976/goldgenomes-online-database</link>
	<title><![CDATA[GOLD:Genomes Online Database]]></title>
	<description><![CDATA[<p><span>GOLD</span><span>:Genomes Online Database, is a World Wide Web resource for comprehensive access to information regarding genome and metagenome sequencing projects, and their associated metadata, around the world.</span></p>
<p>https://gold.jgi.doe.gov/</p><p>Address of the bookmark: <a href="https://gold.jgi.doe.gov/" rel="nofollow">https://gold.jgi.doe.gov/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</guid>
	<pubDate>Wed, 29 Nov 2017 07:40:22 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34482/ribbon-visualizing-complex-genome-alignments-and-structural-variation</link>
	<title><![CDATA[Ribbon: Visualizing complex genome alignments and structural variation:]]></title>
	<description><![CDATA[<p>Ribbon can be used for long reads, short reads, paired-end reads, and assembly/genome alignments. Instructions for each data format are available by clicking on "instructions" in each tab on the right.</p>
<p>Local installation:</p>
<p>You can install Ribbon locally from Github by following the instructions here:&nbsp;<a href="https://github.com/MariaNattestad/ribbon" target="_blank">https://github.com/MariaNattestad/Ribbon</a></p><p>Address of the bookmark: <a href="http://genomeribbon.com/" rel="nofollow">http://genomeribbon.com/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</guid>
	<pubDate>Fri, 08 Dec 2017 16:48:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34569/ksnp30-snp-detection-and-phylogenetic-analysis-of-genomes-without-genome-alignment-or-reference-genome</link>
	<title><![CDATA[kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome]]></title>
	<description><![CDATA[<p><span>Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.&nbsp;<br></span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/ksnp/files/" rel="nofollow">https://sourceforge.net/projects/ksnp/files/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</guid>
	<pubDate>Tue, 26 Dec 2017 22:23:39 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34867/magic-blast-a-tool-for-mapping-large-next-generation-rna-or-dna-sequencing-runs-against-a-whole-genome-or-transcriptome</link>
	<title><![CDATA[Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.]]></title>
	<description><![CDATA[<p>Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.</p>
<p>Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump&nbsp;<a href="http://www.ncbi.nlm.nih.gov/pubmed/26109056">(http://www.ncbi.nlm.nih.gov/pubmed/26109056)</a>, and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.</p><p>Address of the bookmark: <a href="https://ncbi.github.io/magicblast/" rel="nofollow">https://ncbi.github.io/magicblast/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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