<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/34543?offset=150 https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify Tue, 05 Mar 2024 00:23:49 -0600 https://bioinformaticsonline.com/bookmarks/view/44479/doubletrouble-identify-duplicated-genes-from-whole-genome-protein-sequences-and-classify <![CDATA[doubletrouble: identify duplicated genes from whole-genome protein sequences and classify]]> doubletrouble aims to identify duplicated genes from whole-genome protein sequences and classify them based on their modes of duplication. The duplication modes are i. segmental duplication (SD); ii. tandem duplication (TD); iii. proximal duplication (PD); iv. transposed duplication (TRD) and; v. dispersed duplication (DD). Transposon-derived duplicates (TRD) can be further subdivided into rTRD (retrotransposon-derived duplication) and dTRD (DNA transposon-derived duplication). If users want a simpler classification scheme, duplicates can also be classified into SD- and SSD-derived (small-scale duplication) gene pairs. Besides classifying gene pairs, users can also classify genes, so that each gene is assigned a unique mode of duplication. Users can also calculate substitution rates per substitution site (i.e., Ka and Ks) from duplicate pairs, find peaks in Ks distributions with Gaussian Mixture Models (GMMs), and classify gene pairs into age groups based on Ks peaks.

Address of the bookmark: https://bioconductor.org/packages/release/bioc/html/doubletrouble.html

]]> LEGE https://bioinformaticsonline.com/bookmarks/view/26252/recombination-detection-tool Tue, 02 Feb 2016 10:11:14 -0600 https://bioinformaticsonline.com/bookmarks/view/26252/recombination-detection-tool <![CDATA[Recombination detection tool]]> A program to detect recombination hotspots using population genetic data.

More at https://github.com/auton1/LDhot

Address of the bookmark: https://github.com/auton1/LDhot

]]> Jit https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes Wed, 27 Apr 2016 11:07:59 -0500 https://bioinformaticsonline.com/bookmarks/view/27099/rasttk-algorithm-for-building-custom-annotation-pipelines-and-annotating-batches-of-genomes <![CDATA[RASTtk : algorithm for building custom annotation pipelines and annotating batches of genomes]]> The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

More at http://www.nature.com/articles/srep08365

Address of the bookmark: http://rast.nmpdr.org/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping Fri, 20 May 2016 18:53:49 -0500 https://bioinformaticsonline.com/bookmarks/view/27430/mosaik-a-hash-based-algorithm-for-accurate-next-generation-sequencing-short-read-mapping <![CDATA[MOSAIK: A Hash-Based Algorithm for Accurate Next-Generation Sequencing Short-Read Mapping]]> MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090581

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27818/gaemr Tue, 14 Jun 2016 06:18:37 -0500 https://bioinformaticsonline.com/bookmarks/view/27818/gaemr <![CDATA[GAEMR]]> The Genome Assembly Evaluation Metrics and Reporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR’s analysis pipeline, hence enabling the generation of standard reports.

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly. 

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/30680/easybuild Fri, 27 Jan 2017 16:00:43 -0600 https://bioinformaticsonline.com/bookmarks/view/30680/easybuild <![CDATA[EasyBuild]]> EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.
A full list of supported software packages is available here.

Address of the bookmark: https://hpcugent.github.io/easybuild/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data Thu, 14 Dec 2017 15:51:40 -0600 https://bioinformaticsonline.com/bookmarks/view/34678/svfinder-tool-for-detecting-genomic-rearrangement-form-dna-seq-data <![CDATA[SVfinder: Tool for detecting genomic rearrangement form DNA-seq data]]> SVfinder provides genome-wide detection of structural variants from next generation paired-end sequencing reads.

Address of the bookmark: https://github.com/cauyrd/SVfinder

]]> Robert M Willioms https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization Wed, 21 Mar 2018 12:25:20 -0500 https://bioinformaticsonline.com/bookmarks/view/36012/gmol-an-interactive-tool-for-3d-genome-structure-visualization <![CDATA[GMOL: An Interactive Tool for 3D Genome Structure Visualization]]> GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.

Address of the bookmark: https://www.nature.com/articles/srep20802

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42204/g-nest-the-gene-neighborhood-scoring-tool Fri, 25 Sep 2020 20:09:18 -0500 https://bioinformaticsonline.com/bookmarks/view/42204/g-nest-the-gene-neighborhood-scoring-tool <![CDATA[G-NEST: The Gene NEighborhood Scoring Tool]]> The Gene NEighborhood Scoring Tool (G-NEST) combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all window sizes. Primary author of final code = William F. Martin. Example data files are in the separate repository.

Address of the bookmark: https://github.com/dglemay/G-NEST

]]> Neel https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome Thu, 08 Aug 2024 23:31:18 -0500 https://bioinformaticsonline.com/pages/view/44637/tools-to-access-the-quality-of-your-assembled-genome <![CDATA[Tools to access the quality of your assembled genome !]]>
  • FASTA VALIDATOR + SEQKIT RMDUP: FASTA validation
  • GENOMETOOLS GT GFF3VALIDATOR: GFF3 validation
  • ASSEMBLATHON STATS: Assembly statistics
  • GENOMETOOLS GT STAT: Annotation statistics
  • NCBI FCS ADAPTOR: Adaptor contamination pass/fail
  • NCBI FCS GX: Foreign organism contamination pass/fail
  • BUSCO: Gene-space completeness estimation
  • TIDK: Telomere repeat identification
  • LAI: Continuity of repetitive sequences
  • KRAKEN2: Taxonomy classification
  • HIC CONTACT MAP: Alignment and visualisation of HiC data
  • MUMMER → CIRCOS + DOTPLOT & MINIMAP2 → PLOTSR: Synteny analysis
  • MERQURY: K-mer completeness, consensus quality and phasing assessment
    • ]]>     LEGE