BOL: Related items

chromoMap-An R package for Interactive Visualization and Annotation of Chromosomes

Neel — Fri, 12 Apr 2019 05:30:41 -0500

Provides interactive, configurable and elegant graphics visualization of the chromosomes or chromosome regions of any living organism allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. The package provide multiple features like visualizing multiple sets, chromosome heat-maps, group annotations, adding hyperlinks, and labelling. The plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R 'Shiny' applications.

Address of the bookmark: https://cran.r-project.org/web/packages/chromoMap/vignettes/chromoMap.html

DRAM: Distilled and Refined Annotation of Metabolism

BioStar — Sat, 06 Jul 2024 04:19:45 -0500

DRAM (Distilled and Refined Annotation of Metabolism) is a tool for annotating metagenomic assembled genomes and VirSorter identified viral contigs. DRAM annotates MAGs and viral contigs using KEGG (if provided by the user), UniRef90, PFAM, dbCAN, RefSeq viral, VOGDB and the MEROPS peptidase database as well as custom user databases. DRAM is run in two stages. First an annotation step to assign database identifiers to gene, and then a distill step to curate these annotations into useful functional categories. Additionally, viral contigs are further analyzed during to identify potential AMGs. This is done via assigning an auxiliary score and flags representing the confidence that a gene is both metabolic and viral.

Ref https://genomicsaotearoa.github.io/metagenomics_summer_school/day4/ex15_gene_annotation_part3/#overview-of-drampy-annotate-output

Address of the bookmark: https://github.com/WrightonLabCSU/DRAM

dnaPipeTE: de-novo assembly & annotation Pipeline for Transposable Elements

Rahul Nayak — Sat, 02 Dec 2017 18:25:44 -0600

dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (< 1X).

dnaPipeTE is developped by Clément Goubert, Laurent Modolo and the TREEP team of the LBBE: http://lbbe.univ-lyon1.fr/-Equipe-Elements-transposables-.html?lang=en
You can find the original publication in GBE here: https://academic.oup.com/gbe/article/7/4/1192/533768

output examples of quantification and TE landscape (relative age) produced by dnaPipeTE

Address of the bookmark: https://github.com/clemgoub/dnaPipeTE

Detail annotation of genes !

Jit — Fri, 11 Jan 2019 05:23:33 -0600

gene_info recalculated daily
---------------------------------------------------------------------------
tab-delimited
one line per GeneID
Column header line is the first line in the file.
Note: subsets of gene_info are available in the DATA/GENE_INFO
directory (described later)
---------------------------------------------------------------------------

tax_id:
the unique identifier provided by NCBI Taxonomy
for the species or strain/isolate

GeneID:
the unique identifier for a gene
ASN1: geneid

Symbol:
the default symbol for the gene
ASN1: gene->locus

LocusTag:
the LocusTag value
ASN1: gene->locus-tag

Synonyms:
bar-delimited set of unofficial symbols for the gene

dbXrefs:
bar-delimited set of identifiers in other databases
for this gene. The unit of the set is database:value.
Note that HGNC and MGI include 'HGNC' and 'MGI', respectively,
in the value part of their identifier. Consequently,
dbXrefs for these databases will appear like:
HGNC:HGNC:1100
This would be interpreted as database='HGNC', value='HGNC:1100'
Example for MGI:
MGI:MGI:104537
This would be interpreted as database='MGI', value='MGI:104537'

chromosome:
the chromosome on which this gene is placed.
for mitochondrial genomes, the value 'MT' is used.

map location:
the map location for this gene

description:
a descriptive name for this gene

type of gene:
the type assigned to the gene according to the list of options
provided in https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/objects/entrezgene/entrezgene.asn

Symbol from nomenclature authority:
when not '-', indicates that this symbol is from a
a nomenclature authority

Full name from nomenclature authority:
when not '-', indicates that this full name is from a
a nomenclature authority

Nomenclature status:
when not '-', indicates the status of the name from the
nomenclature authority (O for official, I for interim)

Other designations:
pipe-delimited set of some alternate descriptions that
have been assigned to a GeneID
'-' indicates none is being reported.

Modification date:
the last date a gene record was updated, in YYYYMMDD format

Feature type:
pipe-delimited set of annotated features and their classes or
controlled vocabularies, displayed as feature_type:feature_class
or feature_type:controlled_vocabulary, when appropriate; derived
from select feature annotations on RefSeq(s) associated with the
GeneID

Address of the bookmark: ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/

Apollo: a sequence annotation editor

Abhimanyu Singh — Tue, 27 Aug 2019 08:08:47 -0500

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them

Address of the bookmark: https://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-12-research0082

PANNZER: a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function.

BioStar — Thu, 13 Aug 2020 09:57:24 -0500

PANNZER (Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function.

PANNZER (Protein ANNotation with Z-scoRE) is a fully automated service for functional annotation of prokaryotic and eukaryotic proteins of unknown function. The tool is designed to predict the functional description (DE) and GO classes.

PANNZER2 processes bacterial proteomes in minutes and eukaryotic proteomes in an hour. You can use AAI-profiler to summarize a proteome's species neighbors and reveal taxonomic identity or contamination.

Address of the bookmark: http://ekhidna2.biocenter.helsinki.fi/sanspanz/#

QuasR: Quantification and annotation of short reads in R

Neel — Fri, 13 Aug 2021 07:44:05 -0500

The QuasR package (short for Quantify and annotate short reads in R) integrates the functionality of several R packages (such as IRanges (Lawrence et al. 2013) and Rsamtools) and external software (e.g. bowtie, through the Rbowtie package, and HISAT2, through the Rhisat2 package). The package aims to cover the whole analysis workflow of typical high throughput sequencing experiments, starting from the raw sequence reads, over pre-processing and alignment, up to quantification. A single R script can contain all steps of a complete analysis, making it simple to document, reproduce or share the workflow containing all relevant details.

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/QuasR/inst/doc/QuasR.html

DISCO : multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler

Jit — Mon, 10 Jul 2017 10:09:27 -0500

DISCO is a multi threaded and multiprocess distributed memory overlap-layout-consensus (OLC) metagenome assembler. Disco was developed as a scalable assembler to assemble large metagenomes from billions of Illumina sequencing reads of complex microbial communities. Disco was parallelized for computer clusters in a hybrid architecture that integrated shared-memory multi-threading, point-to-point message passing, and remote direct memory access. The assembly and scaffolding were performed using an iterative overlap graph approach.

Address of the bookmark: http://disco.omicsbio.org/

VICUNA: a software tool that enables consensus assembly of ultra-deep sequence derived from diverse viral or other heterogeneous populations.

biogeek — Tue, 25 Aug 2020 03:40:17 -0500

VICUNA is a de novo assembly program targeting populations with high mutation rates. It creates a single linear representation of the mixed population on which intra-host variants can be mapped. For clinical samples rich in contamination (e.g., >95%), VICUNA can leverage existing genomes, if available, to assemble only target-alike reads. After initial assembly, it can also use existing genomes to perform guided merging of contigs. For each data set (e.g., Illumina paired read, 454), VICUNA outputs consensus sequence(s) and the corresponding multiple sequence alignment of constituent reads. VICUNA efficiently handles ultra-deep sequence data with tens of thousands fold coverage.

http://software.broadinstitute.org/viral/docs/vicuna_v1.0.pdf

Address of the bookmark: https://www.broadinstitute.org/viral-genomics/vicuna

EMBL Postdoc position in Bacterial Gene Gain Loss

Thu, 20 Aug 2015 14:09:21 -0500

A post-doctoral fellowship is available in the research groups of Nick Goldman (EBI) and John Welch (Genetics Department, Cambridge University) under the EMBL-EBI / Cambridge Computational Biomedical Postdoctoral Fellowship scheme.

The project is on bacterial gene gain and loss and emerging pathogenicity, and is described in full here: https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015 . The EMBL-EBI / Cambridge Computational Biomedical Postdoctoral (“EBPOD”)

The closing date for applications is 3 September 2015. Nick Goldman EMBL-European Bioinformatics Institute Nick Goldman

More at https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015