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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/42303?offset=40</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35144/converting-fastq-to-fasta</guid>
	<pubDate>Fri, 12 Jan 2018 03:49:09 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35144/converting-fastq-to-fasta</link>
	<title><![CDATA[Converting FASTQ to FASTA]]></title>
	<description><![CDATA[<div id="block-system-main"><div><div><div><div><div><div><p>There are several ways you can convert fastq to fasta sequences. Some methods are listed below.</p><h3>Using SED</h3><p><span><code><span>sed</span></code></span>&nbsp;can be used to selectively print the desired lines from a file, so if you print the first and 2rd line of every 4 lines, you get the sequence header and sequence needed for fasta format.</p><pre>sed -n '1~4s/^@/&gt;/p;2~4p' INFILE.fastq &gt; OUTFILE.fasta
</pre><h3>Using PASTE</h3><p>You can linerize every 4 lines in a tabular format and print first and second field using&nbsp;<span><code>paste</code></span></p><pre>cat INFILE.fastq | paste - - - - |cut -f 1, 2| sed 's/@/&gt;/'g | tr -s "/t" "/n" &gt; OUTFILE.fasta
</pre><h3>EMBOSS:seqret</h3><p>Standard script that can be used for many purposes. One such use is fastq-fasta conversion</p><pre>seqret -sequence reads.fastq -outseq reads.fasta
</pre><p><span><code><span>awk</span></code></span>&nbsp;can be used for conversion as follows:</p><h3>Using AWK</h3><pre>cat infile.fq | awk '{if(NR%4==1) {printf("&gt;%s\n",substr($0,2));} else if(NR%4==2) print;}' &gt; file.fa
</pre><h3>FASTX-toolkit</h3><p><span><code>fastq_to_fasta</code></span>&nbsp;is available in the FASTX-toolkit that scales really well with the huge datasets</p><pre>fastq_to_fasta -h
usage: fastq_to_fasta [-h] [-r] [-n] [-v] [-z] [-i INFILE] [-o OUTFILE]
# Remember to use -Q33 for illumina reads!
version 0.0.6
       [-h]         = This helpful help screen.
       [-r]         = Rename sequence identifiers to numbers.
       [-n]         = keep sequences with unknown (N) nucleotides.
                   Default is to discard such sequences.
       [-v]         = Verbose - report number of sequences.
                   If [-o] is specified,  report will be printed to STDOUT.
                   If [-o] is not specified (and output goes to STDOUT),
                   report will be printed to STDERR.
       [-z]         = Compress output with GZIP.
       [-i INFILE]  = FASTA/Q input file. default is STDIN.
       [-o OUTFILE] = FASTA output file. default is STDOUT.
</pre><h3>Bioawk</h3><p>Another option to convert fastq to fasta format using&nbsp;<span><code>bioawk</code></span></p><pre>bioawk -c fastx '{print "&gt;"$name"\n"$seq}' input.fastq &gt; output.fasta
</pre><h3>Seqtk</h3><p>From the same developer, there is another option using a tool called&nbsp;<span><code>seqtk</code></span></p><pre>seqtk seq -a input.fastq &gt; output.fasta
</pre><p>Note that you can use either compressed or uncompressed files for this tool</p></div></div></div></div></div></div></div>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</guid>
	<pubDate>Mon, 03 Jul 2017 07:52:51 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33789/i-pv-interactive-protein-sequence-visualization</link>
	<title><![CDATA[I-PV: Interactive Protein Sequence Visualization]]></title>
	<description><![CDATA[<p><span>I-PV is a interactive data visualization software designed for inspection of protein sequences and mutation information. It is mainly used for Genetics and Bioinformatics. So what exactly makes it standout?</span></p>
<p><span>http://i-pv.org/ipv_rec</span></p><p>Address of the bookmark: <a href="http://i-pv.org/" rel="nofollow">http://i-pv.org/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</guid>
	<pubDate>Mon, 25 Jun 2018 17:22:24 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37049/chromomap-an-r-package-for-interactive-visualization-and-mapping-of-human-chromosomes</link>
	<title><![CDATA[chromoMap-An R package for Interactive visualization and mapping of human chromosomes]]></title>
	<description><![CDATA[
<p>chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.</p>

<p>https://cran.r-project.org/web/packages/chromoMap/index.html</p>
]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</guid>
	<pubDate>Thu, 12 Aug 2021 00:09:00 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43243/interactive-bioinformatics-resources</link>
	<title><![CDATA[Interactive Bioinformatics Resources !]]></title>
	<description><![CDATA[<p>Learn how to use bioinformatics tools right from your browser.<br>Everything runs in a sandbox, so you can experiment all you want.</p>
<p>More at sandbox.bio</p><p>Address of the bookmark: <a href="http://sandbox.bio" rel="nofollow">http://sandbox.bio</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37788/s-plot2-creates-an-interactive-two-dimensional-heatmap-of-sequences</guid>
	<pubDate>Fri, 28 Sep 2018 05:36:19 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37788/s-plot2-creates-an-interactive-two-dimensional-heatmap-of-sequences</link>
	<title><![CDATA[S-plot2: creates an interactive, two-dimensional heatmap of sequences]]></title>
	<description><![CDATA[<p><span>S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.</span></p>
<p><span>http://www.putonti-lab.com/uploads/4/5/3/0/45307835/s-plot2_tutorial.pdf</span></p>
<p><span>http://journals.sagepub.com/doi/pdf/10.1177/1176934318797354</span></p><p>Address of the bookmark: <a href="https://bitbucket.org/lkalesinskas/splot" rel="nofollow">https://bitbucket.org/lkalesinskas/splot</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39039/dotplotly-generate-an-interactive-dot-plot-from-mummer-or-minimap-alignments</guid>
	<pubDate>Thu, 21 Feb 2019 10:22:17 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39039/dotplotly-generate-an-interactive-dot-plot-from-mummer-or-minimap-alignments</link>
	<title><![CDATA[dotPlotly: Generate an interactive dot plot from mummer or minimap alignments]]></title>
	<description><![CDATA[<p>Create an interactive dot plot from mummer output OR PAF format</p>
<p>R script that makes a plotly interactive and/or static (png/pdf) dot plot.</p>
<p><a href="https://tom-poorten.shinyapps.io/dotplotly_shiny/">Shiny app available for testing</a></p><p>Address of the bookmark: <a href="https://github.com/tpoorten/dotPlotly" rel="nofollow">https://github.com/tpoorten/dotPlotly</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</guid>
	<pubDate>Sat, 29 Feb 2020 00:39:50 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41275/shinychromosomea-gui-for-the-interactive-creation-of-non-circular-whole-genome-diagrams</link>
	<title><![CDATA[shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams]]></title>
	<description><![CDATA[<p><code>shinyChromosome</code> is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R <strong>Shiny</strong> package.</p>
<p>To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the <code>Single-genome plot</code> menu.</p>
<p>To cretae two-genome plot for comparison of data across two genomes, go to the <code>Two-genome plot</code> menu.</p>
<p>For the detail format of input data, check the <code>Input data format</code> submenu of the <code>Help</code> menu.</p>
<p>shinyChromosome is deployed at <a href="http://150.109.59.144:3838/shinyChromosome/" target="_blank">http://150.109.59.144:3838/shinyChromosome/</a>, <a href="http://shinyChromosome.ncpgr.cn" target="_blank">http://shinyChromosome.ncpgr.cn</a>, and <a href="https://yimingyu.shinyapps.io/shinyChromosome" target="_blank">https://yimingyu.shinyapps.io/shinyChromosome</a> for online use. The source code and manual of shinyChromosome are freely available at <a href="https://github.com/venyao/shinyChromosome" target="_blank">https://github.com/venyao/shinyChromosome</a>.</p>
<p>https://yimingyu.shinyapps.io/shinychromosome/</p>
<p>https://www.sciencedirect.com/science/article/pii/S1672022919301883</p><p>Address of the bookmark: <a href="https://yimingyu.shinyapps.io/shinychromosome/" rel="nofollow">https://yimingyu.shinyapps.io/shinychromosome/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36736/checkmassessing-the-quality-of-microbial-genomes-recovered-from-isolates-single-cells-and-metagenomes</guid>
	<pubDate>Wed, 23 May 2018 04:39:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36736/checkmassessing-the-quality-of-microbial-genomes-recovered-from-isolates-single-cells-and-metagenomes</link>
	<title><![CDATA[CheckM:Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes]]></title>
	<description><![CDATA[<p><span>CheckM provides a set of tools for assessing the quality of genomes recovered from isolates, single cells, or metagenomes. It provides robust estimates of genome completeness and contamination by using collocated sets of genes that are ubiquitous and single-copy within a phylogenetic lineage. Assessment of genome quality can also be examined using plots depicting key genomic characteristics (e.g., GC, coding density) which highlight sequences outside the expected distributions of a typical genome. CheckM also provides tools for identifying genome bins that are likely candidates for merging based on marker set compatibility, similarity in genomic characteristics, and proximity within a reference genome tree.</span></p><p>Address of the bookmark: <a href="http://ecogenomics.github.io/CheckM/" rel="nofollow">http://ecogenomics.github.io/CheckM/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies</guid>
	<pubDate>Sat, 06 Jun 2020 05:38:34 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies</link>
	<title><![CDATA[Merqury: reference-free quality and phasing assessment for genome assemblies]]></title>
	<description><![CDATA[<p><span>Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.</span></p>
<p><span><a href="https://github.com/marbl/meryl">https://github.com/marbl/meryl</a></span></p><p>Address of the bookmark: <a href="https://github.com/marbl/merqury" rel="nofollow">https://github.com/marbl/merqury</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</guid>
	<pubDate>Thu, 11 Feb 2021 21:39:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42826/ktrim-an-extra-fast-and-accurate-adapter-and-quality-trimmer-for-sequencing-data</link>
	<title><![CDATA[Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data]]></title>
	<description><![CDATA[<p>Ktrim&nbsp;is written in&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">C++</code>&nbsp;for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">ktrim</code>&nbsp;under&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">bin/</code>&nbsp;directory compiled using&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">g++ v4.8.5</code>&nbsp;and linked with&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz v1.2.7</code>&nbsp;for Linux x86_64 system. If you could not run it (which is usually caused by low version of&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libc++</code>&nbsp;or&nbsp;<code style="font-size: 13.6px; padding: 0.2em 0.4em; margin: 0px; background-color: var(--color-markdown-code-bg);">libz</code>&nbsp;library) or you want to build a version optimized for your system, you can re-compile the programs:</p>
<p>user@linux$ make clean &amp;&amp; make</p><p>Address of the bookmark: <a href="https://github.com/hellosunking/Ktrim" rel="nofollow">https://github.com/hellosunking/Ktrim</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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