<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/34394?offset=120 https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants Tue, 09 Apr 2019 07:23:37 -0500 https://bioinformaticsonline.com/bookmarks/view/39236/causel-an-epigenome-and-genome-editing-pipeline-for-establishing-function-of-noncoding-gwas-variants <![CDATA[CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants]]> Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.

https://www.nature.com/articles/nm.3975

Address of the bookmark: https://www.nature.com/articles/nm.3975

]]> BioJoker https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes Thu, 19 Dec 2019 07:33:40 -0600 https://bioinformaticsonline.com/bookmarks/view/40409/haplotypo-a-variant-calling-pipeline-for-phased-genomes <![CDATA[HaploTypo: a variant-calling pipeline for phased genomes]]> An increasing number of phased (i.e. with resolved haplotypes) reference genomes are available. However, most genetic variant calling tools do not explicitly account for haplotype structure. Here, we present HaploTypo, a pipeline tailored to resolve haplotypes in genetic variation analyses. HaploTypo infers the haplotype correspondence for each heterozygous variant called on a phased reference genome.

Availability and Implementation

HaploTypo is implemented in Python 2.7 and Python 3.5, and is freely available at https://github.com/gabaldonlab/haplotypo, and as a Docker image.

Address of the bookmark: https://github.com/gabaldonlab/haplotypo

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads Fri, 14 Feb 2020 14:23:30 -0600 https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads <![CDATA[SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.]]> This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.

Here is an illustration of this pipeline:

 image

Address of the bookmark: https://github.com/BGI-Qingdao/SLR-superscaffolder

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes Thu, 13 Aug 2020 10:06:19 -0500 https://bioinformaticsonline.com/bookmarks/view/42038/pyparanoid-a-pipeline-for-rapid-identification-of-homologous-gene-families-in-a-set-of-genomes <![CDATA[PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes]]> PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring O(n2) resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.

Address of the bookmark: https://github.com/ryanmelnyk/PyParanoid

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries Sat, 08 May 2021 22:04:02 -0500 https://bioinformaticsonline.com/bookmarks/view/43062/jcvi-utility-libraries <![CDATA[JCVI utility libraries]]> Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

Address of the bookmark: https://github.com/tanghaibao/jcvi

]]> Jit https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data Wed, 06 Sep 2023 00:14:28 -0500 https://bioinformaticsonline.com/bookmarks/view/44375/phyloherb-a-high%E2%80%90throughput-phylogenomic-pipeline-for-processing-genome-skimming-data <![CDATA[PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data]]> Phylogenomic Analysis Pipeline for Herbarium Specimens

What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming.

License: GNU General Public License

Citation:

  • Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1–9. https://doi.org/10.1002/aps3.11475

Address of the bookmark: https://github.com/lmcai/PhyloHerb/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline Sat, 06 Jul 2024 04:32:18 -0500 https://bioinformaticsonline.com/bookmarks/view/44597/imagine-in-silico-metagenomics-pipeline <![CDATA[iMAGine - in silico MetAGenomics pipeline]]> iMAGine is a metagenomic workflow which includes filtering, assembling, and binning.

This workflow includes the following tools which are needed to be installed in the system.

  1. fastp
  2. spades assembler
  3. QUAST
  4. bwa
  5. samtools
  6. metabat2
  7. CheckM

Address of the bookmark: https://github.com/avishekdutta14/iMAGine

]]> BioStar https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology Tue, 19 Dec 2017 18:49:28 -0600 https://bioinformaticsonline.com/news/view/34711/1mb-long-dna-with-nanopore-technology <![CDATA[1mb long DNA with Nanopore technology]]> The first continuous DNA read of more than a million bases (>1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics Thu, 29 Apr 2021 23:39:14 -0500 https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics <![CDATA[CoverM: Read coverage calculator for metagenomics]]> CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.

CoverM calculates coverage of genomes/MAGs coverm genome (help) or individual contigs coverm contig (help). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.

Address of the bookmark: https://github.com/wwood/CoverM

]]> Neel https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus Fri, 05 Jan 2018 04:12:20 -0600 https://bioinformaticsonline.com/bookmarks/view/35061/proovread-large-scale-high-accuracy-pacbio-correction-through-iterative-short-read-consensus <![CDATA[proovread : large-scale high-accuracy PacBio correction through iterative short read consensus]]> proovread : large-scale high-accuracy PacBio correction through iterative short read consensus

proovread maps high coverage data to pacbio reads (bwa mem, blasr, daligner) in multiple iterations.

Address of the bookmark: https://github.com/BioInf-Wuerzburg/proovread

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