<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/41046?offset=90 https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation Wed, 12 Dec 2018 09:16:55 -0600 https://bioinformaticsonline.com/bookmarks/view/38449/koala-keggs-internal-annotation-tool-for-k-number-assignment-of-kegg-genes-using-ssearch-computation <![CDATA[KOALA: KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation]]> KOALA (KEGG Orthology And Links Annotation) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. BlastKOALA and GhostKOALA assign K numbers to the user's sequence data by BLAST and GHOSTX searches, respectively, against a nonredundant set of KEGG GENES. Annotate Sequence in KEGG Mapper and Pathogen Checker in KEGG Pathogen are special interfaces to the BlastKOALA server and can be executed in an interactive mode.    See Step-by-step Instructions.

Reference: Kanehisa, M., Sato, Y., and Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731. [pubmed] [pdf]

Address of the bookmark: https://www.kegg.jp/blastkoala/

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling Fri, 26 Jul 2019 01:11:59 -0500 https://bioinformaticsonline.com/bookmarks/view/39728/patterns-a-modeling-tool-dedicated-to-biological-network-modeling <![CDATA[Patterns: a modeling tool dedicated to biological network modeling]]> It is designed to work with patterned data. Famous examples of problems related to patterned data are:

  • recovering signals in networks after a stimulation (cascade network reverse engineering),
  • analysing periodic signals.

Address of the bookmark: https://github.com/fbertran/Patterns

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny Mon, 17 Feb 2020 05:38:46 -0600 https://bioinformaticsonline.com/bookmarks/view/41125/chromonomer-a-tool-set-for-repairing-and-enhancing-assembled-genomes-through-integration-of-genetic-maps-and-conserved-synteny <![CDATA[Chromonomer: a tool set for repairing and enhancing assembled genomes through integration of genetic maps and conserved synteny]]> Chromonomer is a program designed to integrate a genome assembly with a genetic map. Chromonomer tries very hard to identify and remove markers that are out of order in the genetic map, when considered against their local assembly order; and to identify scaffolds that have been incorrectly assembled according to the genetic map, and split those scaffolds.

Address of the bookmark: http://catchenlab.life.illinois.edu/chromonomer/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs Tue, 30 Jun 2020 21:30:44 -0500 https://bioinformaticsonline.com/bookmarks/view/41916/truvari-structural-variant-comparison-tool-for-vcfs <![CDATA[truvari: Structural variant comparison tool for VCFs]]> Structural variant comparison tool for VCFs

Given benchmark and comparsion sets of SVs, calculate the recall, precision, and f-measure.

Spiral Genetics

Motivation

Address of the bookmark: https://github.com/spiralgenetics/truvari

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42143/sibelia-a-comparative-genomics-tool Sat, 22 Aug 2020 02:49:00 -0500 https://bioinformaticsonline.com/bookmarks/view/42143/sibelia-a-comparative-genomics-tool <![CDATA[Sibelia: A comparative genomics tool]]> Sibelia: A comparative genomics tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms. 

Sibelia is useful in finding: (1) shared regions, (2) regions that present in one group of genomes but not in others, (3) rearrangements that transform one genome to other genomes.

More at http://bioinf.spbau.ru/sibelia

Sibelia docs http://gensoft.pasteur.fr/docs/Sibelia/3.0.7/SIBELIA.md

Address of the bookmark: https://github.com/bioinf/Sibelia

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data Thu, 26 Nov 2020 11:05:04 -0600 https://bioinformaticsonline.com/bookmarks/view/42362/magic-a-tool-for-predicting-transcription-factors-and-cofactors-driving-gene-sets-using-encode-data <![CDATA[MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data]]> The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an a priori binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings:

1) A cell line expressing or lacking single TF,

2) Breast tumors divided along PAM50 designations

3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype

4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels.

In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.

More at https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg

Address of the bookmark: https://github.com/asroopra/MAGIC

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools Thu, 17 Feb 2022 05:37:55 -0600 https://bioinformaticsonline.com/bookmarks/view/43791/comparative-genomics-visualisation-tools <![CDATA[Comparative genomics visualisation tools !]]> Comparative genomics visualisation tools !

Address of the bookmark: https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&selected=%23BRIG&tag=Comparative

]]> Neel https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool Wed, 27 Mar 2024 11:16:24 -0500 https://bioinformaticsonline.com/bookmarks/view/44491/cgviewjs-is-a-circular-genome-viewing-tool <![CDATA[CGView.js is a Circular Genome Viewing tool]]> CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.

CGView.js is the genome viewer of Proksee, an expert system for genome assembly, annotation and visualization.

Features

  • Circular and linear views of genomes

  • Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs

  • Smooth zooming down to the sequence level

  • Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)

  • Save high resolution PNG maps up to 8000x8000px

  • Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes Tue, 10 Sep 2024 04:54:55 -0500 https://bioinformaticsonline.com/bookmarks/view/44655/ngenomesyn-an-easy-to-use-and-flexible-tool-for-publication-ready-visualization-of-syntenic-relationships-across-multiple-genomes <![CDATA[NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes]]> NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes 

image

NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of the whole genome or local region and genomic features (e.g. repeats, structural variations, genes) across multiple genomes with a high customization. NGenomeSyn provides an easy way for its users to visualize a large amount of data with a rich layout by simply adjusting options for moving, scaling, and rotation of target genomes. Moreover, NGenomeSyn could be applied on the visualization of relationships on non-genomic data with similar input formats.

https://academic.oup.com/bioinformatics/article/39/3/btad121/7072460

Address of the bookmark: https://github.com/hewm2008/NGenomeSyn

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output Fri, 15 Apr 2016 05:47:40 -0500 https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output <![CDATA[Understanding Fastqc Output]]> Understanding Following table and graphs

  1. Duplication level
  2. kmer profile
  3. per base GC content
  4. per base N content
  5. per base quality
  6. per base sequence content
  7. per sequence GC content
  8. per sequence quality
  9. sequence length distribution

More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

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