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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/36758?offset=60</link>
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	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</guid>
	<pubDate>Fri, 13 May 2016 04:54:50 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27323/cutadapt</link>
	<title><![CDATA[cutadapt]]></title>
	<description><![CDATA[<p>Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.</p>
<p>Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3&rsquo; sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don&rsquo;t want them to be in your reads.</p>
<p>Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.</p>
<p>Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.</p>
<p>If you use cutadapt, please cite <a href="http://dx.doi.org/10.14806/ej.17.1.200">DOI:10.14806/ej.17.1.200</a> .</p><p>Address of the bookmark: <a href="https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart" rel="nofollow">https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart</a></p>]]></description>
	<dc:creator>Radha Agarkar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</guid>
	<pubDate>Thu, 03 Nov 2016 08:28:25 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/29614/art-set-of-simulation-tools</link>
	<title><![CDATA[ART: Set of Simulation Tools]]></title>
	<description><![CDATA[<p>ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the <span><a href="http://www.1000genomes.org/" target="_blank">1000 Genomes Project<span></span></a></span> . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. <span><a href="http://bioinform.github.io/varsim/" target="_blank">VarSim<span></span></a></span>) for evaluating variant calling tools or methods.</p><p>Address of the bookmark: <a href="http://www.niehs.nih.gov/research/resources/software/biostatistics/art/" rel="nofollow">http://www.niehs.nih.gov/research/resources/software/biostatistics/art/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</guid>
	<pubDate>Mon, 15 May 2017 05:04:39 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/32709/cabog-celera-assembler-with-best-overlap-graph</link>
	<title><![CDATA[CABOG: Celera Assembler with Best Overlap Graph]]></title>
	<description><![CDATA[<p>CABOG (Celera Assembler with Best Overlap Graph) is scientific software for&nbsp;<a href="http://bioinformatics.oxfordjournals.org/content/24/24/2818.abstract">DNA research</a>. CABOG has been a critical component of many genome sequencing projects. CABOG operates on small genomes such as bacterial as well as large genomes such as mammalian. CABOG is an extension of the Celera Assembler software that was originally developed at&nbsp;<a href="http://www.celera.com/">Celera</a>&nbsp;for the 2001 publication of the first draft human genome sequence. The software was released to the public domain in 2004. Its open source&nbsp;<a href="http://wgs-assembler.sf.net/">repository</a>&nbsp;on Source Forge is an internet resource for scientists around the world.&nbsp;</p>
<p>CABOG is one of many software programs called genome assemblers. These programs exist to overcome the fundamental limitation of all sequencing machines, namely, that they read out very few DNA letters at a time. These programs reconstruct genomes that are billions of letters long from the hundreds of letters per read that modern sequencers provide. What these programs do is often described as a scaled up version of a family solving a jigsaw puzzle.</p>
<p>The CABOG software was the first to accomplish many scientific goals. It was the first to assemble the genome of a multicellular organism (<em>Drosophila melanogaster</em>, 2000). It was the first to assemble both parental haplotypes of one human genome (J. Craig Venter, 2007). It was the first to assemble environmental sequence from the oceans (Sargasso Sea in 2004 and Global Ocean Sampling in 2007). It was first to combine reads from first-generation Sanger sequencing machines and second-generation pyrosequencing machines (Marine microbes, 2006). Today, CABOG is one of the leading assembly programs for data sets that include paired end data from the Roche 454 line of sequencing machines.</p><p>Address of the bookmark: <a href="http://www.jcvi.org/cms/research/projects/cabog/overview/" rel="nofollow">http://www.jcvi.org/cms/research/projects/cabog/overview/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</guid>
	<pubDate>Sun, 27 Oct 2019 00:57:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs</link>
	<title><![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]></title>
	<description><![CDATA[<p>Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC:&nbsp;<a href="https://www.biorxiv.org/content/early/2019/01/13/519637">Fast and accurate reference-guided scaffolding of draft genomes</a>.&nbsp;<em>bioRxiv</em>&nbsp;2019.</p>
<p>RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:</p>
<ol>
<li>Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.</li>
<li>Intact ordering and orienting of contigs.</li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Misassembly-Correction">Misassembly correction</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/GFF-File-Lift-Over">GFF lift-over</a></li>
<li><a href="https://github.com/malonge/RaGOO/wiki/Calling-Structural-Variants">Structural variant calling with and integrated version of Assemblytics</a></li>
<li>Confidence scores associated with the grouping, localization, and orientation for each contig.</li>
</ol><p>Address of the bookmark: <a href="https://github.com/malonge/RaGOO" rel="nofollow">https://github.com/malonge/RaGOO</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</guid>
	<pubDate>Thu, 24 Mar 2022 19:48:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43828/understanding-hifi-reads</link>
	<title><![CDATA[Understanding HiFi Reads !]]></title>
	<description><![CDATA[<p><span>While little public data is available for either of the new synthetic long read approaches, Illumina showed an example comparison earlier this year at the&nbsp;</span><a href="https://www.festivalofgenomics.com/rami-mehio" target="_blank">Festival of Genomics &amp; Biodata conference</a><span>&nbsp;(FoG 2022). In the IGV screenshot presented (below), synthetic Infinity reads &ndash; labeled &ldquo;Longas&rdquo; &ndash; are at the top, followed by standard Illumina short reads, and PacBio HiFi reads labeled &ldquo;CCS&rdquo; depicted at the bottom:</span></p><p>Address of the bookmark: <a href="http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/" rel="nofollow">http://pacb.com/blog/the-hifi-difference-true-long-reads-vs-synthetic-long-reads/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</guid>
	<pubDate>Tue, 18 Sep 2018 07:52:41 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37737/rebaler-program-for-conducting-reference-based-assemblies-using-long-reads</link>
	<title><![CDATA[Rebaler: program for conducting reference-based assemblies using long reads.]]></title>
	<description><![CDATA[<p>Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on&nbsp;<a href="https://github.com/lh3/minimap2">minimap2</a>&nbsp;for alignment and&nbsp;<a href="https://github.com/isovic/racon">Racon</a>&nbsp;for making consensus sequences.</p>
<p>I made Rebaler for bacterial genomes (specifically for the task of&nbsp;<a href="https://github.com/rrwick/Basecalling-comparison">testing basecallers</a>). It should in principle work for non-bacterial genomes as well, but I haven't tested it.</p><p>Address of the bookmark: <a href="https://github.com/rrwick/Rebaler" rel="nofollow">https://github.com/rrwick/Rebaler</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</guid>
	<pubDate>Thu, 09 Mar 2023 02:56:54 -0600</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44234/steps-to-find-palindrome-in-genomes</link>
	<title><![CDATA[Steps to find palindrome in genomes !]]></title>
	<description><![CDATA[<div><div><div><div><div><div><div><div><div><div><p>Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:</p><ol>
<li>
<p>Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.</p>
</li>
<li>
<p>Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.</p>
</li>
<li>
<p>Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.</p>
</li>
<li>
<p>Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.</p>
</li>
<li>
<p>Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.</p>
</li>
</ol><p>Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.</p></div></div></div></div></div></div></div></div></div></div>]]></description>
	<dc:creator>BioStar</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/39302/understanding-reads-mapping-and-flags</guid>
	<pubDate>Thu, 25 Apr 2019 09:06:20 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/39302/understanding-reads-mapping-and-flags</link>
	<title><![CDATA[Understanding reads mapping and flags !]]></title>
	<description><![CDATA[<p><strong>Linear Alignment:</strong>&nbsp;An alignment of a read to a single reference sequence that may&nbsp;<q>include insertions, deletions, skips and clipping</q>,&nbsp;<span style="text-decoration: underline;">but may not include direction changes</span>&nbsp;(i.e. one portion of the alignment on forward strand and another portion of alignment on reverse strand).<sup id="fnref:1"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:1"><br /></a></sup></p><p><strong>Chimeric Alignment:</strong>&nbsp;An alignment of a read that cannot be represented as a linear alignment. Typically, one of the linear alignments in a chimeric alignment is considered the &ldquo;representative&rdquo; alignment, and the others are called &ldquo;supplementary&rdquo; and are distinguished by the supplementary alignment flag.<sup id="fnref:1:1"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:1"><br /></a></sup></p><p>Chimeric reads are indicative of structural variation in DNA-seq and it may indicate the presence of&nbsp;<a href="https://en.wikipedia.org/wiki/Chimeric_gene">chimeric genes</a>&nbsp;in RNA-seq.<sup id="fnref:2"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:2"><br /></a></sup></p><p>In short, chimeric reads can be split in to two or more parts, each part would be mapped to reference(it&rsquo;s not&nbsp;<a href="https://www.biostars.org/p/119537/">hard-clipped</a>), the total length of the mapped part is longger than read length.<sup id="fnref:3"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:3"><br /></a></sup></p><p><strong>Representative alignment:</strong>&nbsp;A chimeric alignment that is represented as a set of linear alignments that do not have large overlaps typically has one linear alignment that is considered the representative alignment.<sup id="fnref:4"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:4"><br /></a></sup></p><p>One read can align to multiple positions, we can find one alignmnet position which sequence do not have large overlaps, it called representative alighment, for other alignment positions, we called them supplementary alignment.</p><p>It seems that GATK can realignment those representative reads to the correctly position via&nbsp;<q>RealignerTargetCreator and IndelRealigner</q>. (WARNING: I am not quite sure if I understand this correctly. If someone could help me, please leave me a message below, thanks, thanks.)</p><p><strong>Supplementary Alignment:</strong>&nbsp;A chimeric reads but not a representative reads.</p><p><strong>Primary Alignment and Secondary Alignment:</strong>&nbsp;A read may map ambiguously to multiple locations, e.g. due to repeats.&nbsp;<strong>Only one of the multiple read alignments is considered primary</strong>,<span style="text-decoration: underline;">&nbsp;and this decision may be arbitrary</span>. All other alignments have the secondary alignment flag.<sup id="fnref:5"><a href="https://yulijia.net/en/bioinformatics/2015/12/21/Linear-Chimeric-Supplementary-Primary-and-Secondary-Alignments.html#fn:5"><br /></a></sup></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</guid>
	<pubDate>Tue, 19 Jun 2018 08:34:15 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/36974/many-to-many-pairwise-alignments-of-two-sequence-sets</link>
	<title><![CDATA[Many-to-many pairwise alignments of two sequence sets]]></title>
	<description><![CDATA[needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.<p>Address of the bookmark: <a href="http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html" rel="nofollow">http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html</a></p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38389/blast-options-setting-and-defaults</guid>
	<pubDate>Mon, 10 Dec 2018 08:29:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38389/blast-options-setting-and-defaults</link>
	<title><![CDATA[BLAST options, setting and defaults]]></title>
	<description><![CDATA[<p>BLAST stands for Basic Local Alignment Search Tool and was developed by Altschul et al. (1990) and significantly improved by&nbsp;<a href="http://www3.oup.co.uk/nar/Volume_25/Issue_17/freepdf/">Altschul et al. (1997).</a>&nbsp;It is a very fast search algorithm that is used to separately search protein or DNA databases. BLAST is best used for sequence similarity searching, rather than for motif searching. For searches using a query sequence of fewer than twenty residues,&nbsp;<a href="https://www.arabidopsis.org/servlets/tools/patmatch/">PatMatch</a>&nbsp;is the best choice. Another sequence alignment tool that may yield different results from BLAST, and may be useful for motif searching, is&nbsp;<a href="https://www.arabidopsis.org/cgi-bin/fasta/TAIRfasta.pl">FASTA</a>. To search nonplant datasets, try&nbsp;<a href="http://seqsim.ncgr.org/newBlast.html">NCGR BLAST</a>&nbsp;or&nbsp;<a href="http://www.ncbi.nlm.nih.gov/blast/blast.cgi?Jform=0">NCBI BLAST</a>.</p>
<p>A fairly complete on-line guide to BLAST searching can be found at the&nbsp;<a href="http://www.ncbi.nlm.nih.gov/BLAST/blast_help.html">NCBI BLAST Help Manual</a>. For a theoretical overview of BLAST, see the&nbsp;<a href="http://www.ncbi.nlm.nih.gov/BLAST/tutorial/Altschul-1.html">NCBI BLAST Course</a>. Additional information can be found in the&nbsp;<a href="https://www.arabidopsis.org/blast/aboutblast2.htm">BLAST 2.0 Release Notes</a></p>
<table border="1">
<tbody>
<tr><th>&nbsp;</th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">BLASTN</a></th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">BLASTP</a></th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">BLASTX</a></th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">TBLASTN</a></th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">TBLASTX</a></th><th><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#methods">PSIBLAST</a></th></tr>
<tr>
<td><a name="open" id="open"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#open"><strong>Gap opening penalty</strong></a>:<br>cost to open a gap [integer]</td>
<td align="center">default = 5</td>
<td align="center">default = 11<br>limited&nbsp;values&nbsp;are supported</td>
<td align="center">default = 11<br>limited&nbsp;values&nbsp;are supported</td>
<td align="center">default = 11<br>limited&nbsp;values&nbsp;are supported</td>
<td align="center">default = 11<br>limited&nbsp;values&nbsp;are supported</td>
<td align="center">default = 5</td>
</tr>
<tr>
<td><a name="extend" id="extend"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#extend"><strong>Gap extension penalty</strong></a>:<br>cost to extend a gap [integer]</td>
<td align="center">default = 2</td>
<td align="center">default = 1<br>a 0 in this field means to use the default</td>
<td align="center">default = 1<br>a 0 in this field means to use the default</td>
<td align="center">default = 1<br>a 0 in this field means to use the default</td>
<td align="center">default = 1<br>a 0 in this field means to use the default</td>
<td align="center">default = 2</td>
</tr>
<tr>
<td><a name="match" id="match"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#match"><strong>Nucleic match</strong></a>:<br>reward for a match in the BLAST portion of run [integer]</td>
<td align="center">default = 1</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">default = 1</td>
</tr>
<tr>
<td><a name="mismatch" id="mismatch"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#mismatch"><strong>Nucleic mismatch</strong></a>:<br>penalty for a mismatch in the blast portion of run [integer]</td>
<td align="center">default = -3</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">default = -3</td>
</tr>
<tr>
<td><strong><a name="expect" id="expect"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#expect">Expectation value</a></strong>:<br>(E) [real]</td>
<td align="center">default = 10.0</td>
<td align="center">default = 10.0</td>
<td align="center">default = 10.0</td>
<td align="center">default = 10.0</td>
<td align="center">default = 10.0</td>
<td align="center">default = 10.0</td>
</tr>
<tr>
<td><a name="word" id="word"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#word"><strong>Word size</strong></a>:<br>the size of the initial word that must be matched between the database and the query sequence</td>
<td align="center">default = 11</td>
<td align="center">default = 3</td>
<td align="center">default = 3</td>
<td align="center">default = 3</td>
<td align="center">default = 3</td>
<td align="center">default = 11</td>
</tr>
<tr>
<td><a name="descriptions" id="descriptions"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#descriptions"><strong>Max scores</strong></a>:<br>Number of one-line descriptions (V) [Integer]</td>
<td align="center">default = 25</td>
<td align="center">default = 25</td>
<td align="center">default = 25</td>
<td align="center">default = 25</td>
<td align="center">default = 25</td>
<td align="center">default = 25</td>
</tr>
<tr>
<td><strong><a name="alignments" id="alignments"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#alignments">Max alignments</a></strong>:<br>number of alignments to show (B) [integer]</td>
<td align="center">default = 15</td>
<td align="center">default = 15</td>
<td align="center">default = 15</td>
<td align="center">default = 15</td>
<td align="center">default = 15</td>
<td align="center">default = 15</td>
</tr>
<tr>
<td><strong>Query filter</strong>:<br>filter applied to the query sequence</td>
<td align="center">default = DUST</td>
<td align="center">default = SEG</td>
<td align="center">default = SEG</td>
<td align="center">default = SEG</td>
<td align="center">default = SEG</td>
<td align="center">default = DUST</td>
</tr>
<tr>
<td><strong><a name="gencodes" id="gencodes"></a><a href="https://www.arabidopsis.org/Blast/BLAST_help.jsp#gencodes">Query genetic code</a></strong>:<br>genetic code to be used in BLASTX translation of the query</td>
<td align="center">n/a</td>
<td align="center">n/a</td>
<td align="center">default = universal</td>
<td align="center">default = universal</td>
<td align="center">default = universal</td>
<td align="center">n/a</td>
</tr>
<tr>
<td><strong><a name="matrix" id="matrix"></a><a href="http://twod.med.harvard.edu/seqanal/matrices.html">Matrix</a></strong>:<br>substitution matrix to be used for amino acid comparisons</td>
<td align="center">no default</td>
<td align="center">default = blosum62</td>
<td align="center">default = blosum62</td>
<td align="center">default = blosum62</td>
<td align="center">default = blosum62</td>
<td align="center">no default</td>
</tr>
</tbody>
</table>
<p>Supported and Suggested&nbsp;Values&nbsp;for Gap Open and Extension in BLASTP, BLASTX, TBLASTN, and TBLASTX</p>
<table border="1">
<tbody>
<tr><th>Gaps Open</th><th>Gap Extension</th></tr>
<tr>
<td align="center">10</td>
<td align="center">1</td>
</tr>
<tr>
<td align="center">10</td>
<td align="center">2</td>
</tr>
<tr>
<td align="center">11</td>
<td align="center">1</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">2</td>
</tr>
<tr>
<td align="center">9</td>
<td align="center">2</td>
</tr>
</tbody>
</table><p>Address of the bookmark: <a href="https://www.arabidopsis.org/Blast/BLASToptions.jsp" rel="nofollow">https://www.arabidopsis.org/Blast/BLASToptions.jsp</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>