<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/43353?offset=10 https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing Wed, 06 Dec 2017 01:05:21 -0600 https://bioinformaticsonline.com/bookmarks/view/34525/hic-pro-an-optimized-and-flexible-pipeline-for-hi-c-data-processing <![CDATA[HiC-Pro: an optimized and flexible pipeline for Hi-C data processing]]> HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.

 

http://nservant.github.io/HiC-Pro/

Address of the bookmark: http://nservant.github.io/HiC-Pro/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/38067/metaplotr-a-perlr-pipeline-for-plotting-metagenes-of-nucleotide-modifications-and-other-transcriptomic-sites Mon, 05 Nov 2018 08:12:45 -0600 https://bioinformaticsonline.com/bookmarks/view/38067/metaplotr-a-perlr-pipeline-for-plotting-metagenes-of-nucleotide-modifications-and-other-transcriptomic-sites <![CDATA[MetaPlotR: a Perl/R pipeline for plotting metagenes of nucleotide modifications and other transcriptomic sites]]> An increasing number of studies are mapping protein binding and nucleotide modifications sites throughout the transcriptome. Often, these sites cluster in certain regions of the transcript, giving clues to their function. Hence, it is informative to summarize where in the transcript these sites occur. A metagene is a simple and effective tool for visualizing the distribution of sites along a simplified transcript model. In this work, we introduce MetaPlotR, a Perl/R pipeline for creating metagene plots.

Address of the bookmark: https://github.com/olarerin/metaPlotR

]]> Neel https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates Thu, 16 May 2019 00:17:39 -0500 https://bioinformaticsonline.com/bookmarks/view/39370/multiphate-bioinformatics-pipeline-for-functional-annotation-of-phage-isolates <![CDATA[multiPhATE: bioinformatics pipeline for functional annotation of phage isolates]]> multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases. 

 

Address of the bookmark: https://github.com/carolzhou/multiPhATE

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output Fri, 24 Jan 2020 06:04:40 -0600 https://bioinformaticsonline.com/bookmarks/view/40604/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output <![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]> gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser.

gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/41675/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output Thu, 14 May 2020 15:13:30 -0500 https://bioinformaticsonline.com/bookmarks/view/41675/gapfinisher-a-reliable-gap-filling-pipeline-for-sspace-longread-scaffolder-output <![CDATA[gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output]]> gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/

Address of the bookmark: https://github.com/kammoji/gapFinisher

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins Mon, 17 Aug 2020 05:25:10 -0500 https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins <![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]> SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:

  1. Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
  2. Co-assembly of a large number of metagenomes via merging of individual metagenomes
  3. Includes binning and bin checking, for retrieving individual genomes
  4. The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
  5. Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
  6. Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

]]> 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/bookmarks/view/40996/sequanix-a-dynamic-graphical-interface-for-snakemake-workflows Wed, 12 Feb 2020 01:20:34 -0600 https://bioinformaticsonline.com/bookmarks/view/40996/sequanix-a-dynamic-graphical-interface-for-snakemake-workflows <![CDATA[Sequanix: a dynamic graphical interface for Snakemake workflows]]>
  • A Python library dedicated to NGS analysis (e.g., tools to visualise standard NGS formats).
  • A set of pipelines dedicated to NGS in the form of Snakefiles (Makefile-like with Python syntax based on snakemake framework) with more than 80 re-usable rules (see Rules).
  • Original tools to help in the creation of such pipelines including HTML reports.
  • Standalone applications:
    1. sequana_coverage ease the extraction of genomic regions of interest and genome coverage information
    2. sequana_taxonomy performs a quick taxonomy of your FastQ. This requires dedicated databases to be downloaded.
    3. Sequanix: GUI for snakemake workflows, a GUI for Snakemake workflows (hence Sequana pipelines as well)

    More at https://sequana.readthedocs.io/en/master/

    • Address of the bookmark: https://github.com/sequana/sequana

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