<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/40699?offset=300 https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics Thu, 26 Jul 2018 04:58:45 -0500 https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics <![CDATA[My commonly used commands in Bioinformatics]]> FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:

minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta

This reports Racon's changes in a table. You can exclude indels with the -I option in show-snps. 

This process (Racon -> MUMmer -> SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores Sun, 04 Nov 2018 16:44:30 -0600 https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores <![CDATA[Referee: Genome assembly quality scores]]> Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.

We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.

Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.

https://github.com/gwct/referee

Address of the bookmark: https://gwct.github.io/referee/#

]]> Jit https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator Fri, 26 Jul 2019 00:58:12 -0500 https://bioinformaticsonline.com/bookmarks/view/39726/jackalope-a-swift-versatile-phylogenomic-and-high-throughput-sequencing-simulator <![CDATA[jackalope: A swift, versatile phylogenomic and high-throughput sequencing simulator]]> jackalope simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants can be simulated using summary statistics, phylogenies, Variant Call Format (VCF) files, and coalescent simulations—the latter of which can include selection, recombination, and demographic fluctuations. jackalope can simulate single, paired-end, or mate-pair Illumina reads, as well as reads from Pacific Biosciences These simulations include sequencing errors, mapping qualities, multiplexing, and optical/PCR duplicates. All outputs can be written to standard file formats.

A swift, versatile phylogenomic and high-throughput sequencing simulator https://jackalope.lucasnell.com

Address of the bookmark: https://github.com/lucasnell/jackalope

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping Wed, 29 Jan 2020 06:29:55 -0600 https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping <![CDATA[Understanding your reads and mapping !]]> One of the best tutorial for beginners ...

https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

Address of the bookmark: https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

]]> Neel https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies Sat, 06 Jun 2020 05:38:34 -0500 https://bioinformaticsonline.com/bookmarks/view/41831/merqury-reference-free-quality-and-phasing-assessment-for-genome-assemblies <![CDATA[Merqury: reference-free quality and phasing assessment for genome assemblies]]> 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.

https://github.com/marbl/meryl

Address of the bookmark: https://github.com/marbl/merqury

]]> Jit https://bioinformaticsonline.com/news/view/4191/high-density-sheep-snp-genotyping-chip-released Tue, 03 Sep 2013 13:58:04 -0500 https://bioinformaticsonline.com/news/view/4191/high-density-sheep-snp-genotyping-chip-released <![CDATA[High Density Sheep SNP Genotyping Chip released!!!]]> If you are working on Sheep genomics then there is a good news for you. FarmIQ in conjunction with Illumina and the International Sheep Genomics Consortium (ISGC) are today announcing completion of the “Ovine Infinium® HD SNP BeadChip”, a high definition SNP chip for ship genome. The OvineSNP50 BeadChip features over 54,241 evenly spaced probes that target SNPs, offering more than sufficient SNP density for genome-wide association studies and other applications such as genome-wide selection, determination of genetic merit, identification of quantitative trait loci, and comparative genetic studies.

The BeadChip was developed in collaboration with leading ovine researchers from AgResearch, Baylor UCSC, CSIRO, and the USDA as part of the International Sheep Genomics Consortium. It features over 54,241 evenly spaced probes that target single nucleotide polymorphisms (SNPs). More than 18,000 of these markers were discovered through sequencing reduced representation libraries with the Illumina Genome Analyzer IIx. A set of 600 SNPs were identified by BAC end sequencing and validated with Illumina GoldenGate Genotyping Assays over 403 animals from 23 breeds. The remaining SNPs were derived from the draft ovine genome.

Read more @

http://res.illumina.com/documents/products/datasheets/datasheet_ovinesnp50.pdf

http://www.illumina.com/products/ovinesnp50_dna_analysis_kit.ilmn

]]> Rahul Agarwal https://bioinformaticsonline.com/opportunity/view/26432/summer-2016 Sun, 21 Feb 2016 06:17:55 -0600 <![CDATA[Summer 2016]]> REU at Fordham University- Summer 2016

An NSF-funded REU to study Y-chromosome diversity and sex-biased dispersal in wild brown rats (Rattus norvegicus) is available in the Munshi-South Lab at Fordham University. Our lab is currently investigating rat evolution at scales ranging from landscape genetics of individual cities to global patterns of diversity. Development of resources for investigating Y-chromosome diversity will support many of these studies. The REU student will work with the lab to bioinformatically identify Y-chromosome SNPs, design SNPtype assays,
extract DNA, genotype samples, and analyze data.

We seek applicants interested in bioinformatics, evolutionary biology, and related disciplines. Applicants must have taken a college-level genetics course. This REU will require attention to detail, reliability, independence, and critical thinking.

This position is based at Fordham University's field station, the Louis Calder Center, in Armonk, NY. The Calder Center is located approximately 25 miles north of New York City in a protected woodland area. Housing
will be provided at the Calder Center for the duration of the REU (May 23 to Aug 12, 2016). Additionally, the student will receive a $6,000 stipend. The selected student will participate in professional development activities through the Calder Centers REU program, including presentation of results at a research colloquium at the end of the summer.

To apply, please send a one page personal statement about your scientific interests and how this REU will support your professional goals, unofficial transcripts including a list of Spring 2016 courses, and names of two professional references (including title, address, phone number, and email address) as a single pdf (with your last name in the file name) to Dr. Jason Munshi-South (jmunshisouth@fordham.edu).

Applications are due March 4th, 2016.

Jason Munshi-South

]]> https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model Fri, 28 Feb 2020 23:27:37 -0600 https://bioinformaticsonline.com/bookmarks/view/41272/rainbowr-reliable-association-inference-by-optimizing-weights-with-r-r-package-for-snp-set-gwas-and-multi-kernel-mixed-model <![CDATA[RAINBOWR: Reliable Association INference By Optimizing Weights with R (R package for SNP-set GWAS and multi-kernel mixed model)]]> RAINBOWR(Reliable Association INference By Optimizing Weights with R) is a package to perform several types of GWAS as follows.

  • Single-SNP GWAS with RGWAS.normal function
  • SNP-set (or gene set) GWAS with RGWAS.multisnp function (which tests multiple SNPs at the same time)
  • Check epistatic (SNP-set x SNP-set interaction) effects with RGWAS.epistasis (very slow and less reliable)

https://github.com/KosukeHamazaki/RAINBOWR

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663

https://cran.r-project.org/web/packages/RAINBOWR/index.html

Address of the bookmark: https://github.com/KosukeHamazaki/RAINBOWR

]]> Surabhi Chaudhary https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment Mon, 05 Aug 2024 23:01:29 -0500 https://bioinformaticsonline.com/bookmarks/view/44628/uncovar-workflow-for-transparent-and-robust-virus-variant-calling-genome-reconstruction-and-lineage-assignment <![CDATA[UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment]]> UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

  • Using state of the art tools, easily extended for other viruses

  • Tool and database updates for critical components via Conda

  • Built using modern design patterns with Conda and Snakemake

  • Extensible and easy to customize

  • Submission Ready Genomes

  • Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

 

 

Address of the bookmark: https://ikim-essen.github.io/uncovar/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data Tue, 28 Jan 2020 03:44:43 -0600 https://bioinformaticsonline.com/bookmarks/view/40707/vt-a-variant-tool-set-that-discovers-short-variants-from-next-generation-sequencing-data <![CDATA[vt: a variant tool set that discovers short variants from Next Generation Sequencing data.]]> vt is a variant tool set that discovers short variants from Next Generation Sequencing data.

https://genome.sph.umich.edu/wiki/Vt

https://github.com/atks/vt

Address of the bookmark: https://genome.sph.umich.edu/wiki/Vt

]]> Jit