BOL: Related items

Genome Annotation Transfer Utility (GATU)

Jit — Mon, 29 May 2017 05:54:53 -0500

Genome Annotation Transfer Utility (GATU) was designed to facilitate quick, efficient annotation of similar genomes using genomes that have already been annotated. For example, whenever a new strain of SARS coronavirus is sequenced, it is possible, using GATU, to automatically annotate the new strain using a previously-annotated strain of SARS CoV. This saves researchers from tedious manual annotation of these sequences.

The program utilizes tBLASTn and BLASTn algorithms to map genes from the reference genome (the annotated strain) to the new sequence (the unannotated strain). The goal is to annotate the majority of the new genome’s genes in a single step. ORFs present in the target genome and absent from the reference genome are also identified; these ORFs can be further analyzed using BLAST, VGO and BBB. Afterwards, they can either be accepted for/rejected from annotation. GATU can handle multiple-exon genes as well as mature peptides. Although it was designed for use with viral genomes, GATU can also be used to help annotate larger genomes (ie. bacterial genomes).

The output is saved in GenBank, XML, or EMBL file format.

Address of the bookmark: https://virology.uvic.ca/help/tool-help/help-books/genome-annotation-transfer-utility-gatu-documentation/

REGEN: Ancestral Genome Reconstruction for Bacteria

Rahul Nayak — Tue, 06 Mar 2018 05:02:36 -0600

REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order.

Address of the bookmark: http://www.mdpi.com/2073-4425/3/3/423

Jvarkit : Java utilities for Bioinformatics

Jit — Fri, 08 Jun 2018 09:31:55 -0500

Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

Address of the bookmark: http://lindenb.github.io/jvarkit/

You can't hide from Genome Hackers

Neel — Sat, 13 Oct 2018 14:17:28 -0500

Young computational biologist named Yaniv Erlich shocked the research world by showing it was possible to unmask the identities of people listed in anonymous genetic databases using only an Internet connection

Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832

More at https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/

Genome Annotation using MAKER tutorial !

Shruti Paniwala — Thu, 20 Dec 2018 17:39:23 -0600

MAKER is a great tool for annotating a reference genome using empirical and ab initiogene predictions. GMOD, the umbrella organization that includes MAKER, has some nice tutorials online for running MAKER. However, these were quite simplified examples and it took a bit of effort to wrap my head completely around everything. Here I will describe a de novo genome annotation for Boa constrictor in detail, so that there is a record and that it is easy to use this as a guide to annotate any genome.

Address of the bookmark: https://www.biostars.org/p/261203/

Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup

Jit — Sat, 13 Apr 2019 08:55:31 -0500

Darwin-WGA, is the first hardware accelerator for whole genome alignment and accelerates the gapped filtering stage. Darwin-WGA also employs GACT-X, a novel algorithm used in the extension stage to align arbitrarily long genome sequences using a small on-chip memory, that provides better quality alignments at 2× improvement in memory and speed over the previously published GACT algorithm. Implemented on an FPGA, Darwin-WGA provides up to 24× improvement (performance/$) in WGA over iso-sensitive software.

https://stanford.edu/~yatisht/pubs/darwin-wga.pdf

Address of the bookmark: https://github.com/gsneha26/Darwin-WGA

Genome Informatics Section Lab !

Sat, 25 Jan 2020 06:38:23 -0600

Our section develops and applies computational methods for the analysis of massive genomics datasets, focusing on the challenges of genome sequencing and comparative genomics. We aim to improve such foundational processes and translate emerging genomic technologies into practice.

The Genome Informatics Section is hiring! Come join our outstanding team at the NIH’s National Human Genome Research Institute and contribute to the development of new reference genomes and computational methods for DNA sequencing and analysis. Both postdoc and PhD students positions are available. More information and application instructions follow below.

More at https://genomeinformatics.github.io/

Simons Genome Diversity Project

Jit — Sat, 08 May 2021 21:55:25 -0500

Complete genome sequences from more than one hundred diverse human populations

All genomes in the dataset were sequenced to at least 30x coverage using Illumina technology. The sequencing reads were mapped and genotyped using a customized procedure that was optimized for population genetic analysis. The researchers eliminated bias of alleles toward matching the human genome reference sequence, and determined genotypes on a single-sample basis to avoid preferential calling of genotypes from populations that had more individuals represented.

Address of the bookmark: https://www.simonsfoundation.org/simons-genome-diversity-project/

UniqueKmer: Generate unique KMERs for every contig in a FASTA file

Abhi — Fri, 17 Dec 2021 00:08:15 -0600

Generate unique k-mers for every contig in a FASTA file.

Unique k-mer is consisted of k-mer keys (i.e. ATCGATCCTTAAGG) that are only presented in one contig, but not presented in any other contigs (for both forward and reverse strands).

This tool accepts the input of a FASTA file consisting of many contigs, and extract unique k-mers for each contig.

The output unique k-mer file and Genome file can be used for fastv: https://github.com/OpenGene/fastv, which is an ultra-fast tool to identify and visualize microbial sequences from sequencing data.

https://github.com/OpenGene/UniqueKMER

Address of the bookmark: https://github.com/OpenGene/UniqueKMER

The ATCC Genome Portal

Abhi — Wed, 15 May 2024 14:24:16 -0500

The ATCC Genome Portal (AGP, https://genomes.atcc.org/) is a database of authenticated genomes for bacteria, fungi, protists, and viruses held in ATCC’s biorepository. It now includes 3,938 assemblies (253% increase) produced under ISO 9000 by ATCC. Here, we present new features and content added to the AGP for the research community.

Address of the bookmark: https://genomes.atcc.org/