BOL: Related items

TwinBLAST: When Two Is Better than One

Jit — Sat, 07 Sep 2019 08:50:08 -0500

TwinBLAST is a web-based tool for viewing 2 BLAST reports simultaneouslyside-by-side. It uses ExtJS (www.sencha.com/products/extjs/) to provide 2independently scrollable panels. BioPerl (www.bioperl.org) is used to indexraw BLAST reports and Bio::Graphics is used to draw pictograms of the BLASThits.

https://github.com/IGS/twinblast

https://mra.asm.org/content/8/35/e00842-19

Address of the bookmark: https://github.com/IGS/twinblast

SOWDHAMINI Lab

Sun, 15 Sep 2013 09:19:12 -0500

Genome sequencing projects have enormous potential for benefiting human endeavors. However, just as acquiring a language's vocabulary does not enable one to speak it, databases that list the amino acid composition of proteins do not directly tell us much about these proteins' higher-level structure and function. The most productive way to indirectly exploit these databases has been to start with the small number of proteins that are fully-characterised and to assume that other "similar" proteins will have a related structure and function. Proteins with very similar amino acid sequence are "no-brainers", but the real test, which our group largely focuses on, is to detect the "essential" similarity in proteins whose non-critical sections have experienced random rearrangements during evolution. In such cases functionally similar proteins may have less than 25% sequence overlap.

More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm

FastANI: fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI)

Jit — Fri, 13 Jul 2018 17:27:01 -0500

FastANI is developed for fast alignment-free computation of whole-genome Average Nucleotide Identity (ANI). ANI is defined as mean nucleotide identity of orthologous gene pairs shared between two microbial genomes. FastANI supports pairwise comparison of both complete and draft genome assemblies. Its underlying procedure follows a similar workflow as described by Goris et al. 2007. However, it avoids expensive sequence alignments and uses Mashmap as its MinHash based sequence mapping engine to compute the orthologous mappings and alignment identity estimates. Based on our experiments with complete and draft genomes, its accuracy is on par with BLAST-based ANI solver and it achieves two to three orders of magnitude speedup. Therefore, it is useful for pairwise ANI computation of large number of genome pairs. More details about its speed, accuracy and potential applications are described here: "High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries".

Address of the bookmark: https://github.com/ParBLiSS/FastANI

FGENESH - Program for predicting multiple genes in genomic DNA sequences

BioStar — Thu, 20 Dec 2018 11:55:08 -0600

FGENESH is the fastest (50-100 times faster than GenScan) and most accurate gene finder available - see the figure and the table below. In recent rice genome sequencing projects, it was cited "the most successful (gene finding) program (Yu et al. (2002) Science 296:79) and was used to produce 87% of all high-evidence predicted genes (Goff et al. (2002) Science 296:79).

Address of the bookmark: http://www.softberry.com/berry.phtml?topic=fgenesh&group=help&subgroup=gfind

Flanker

Rahul Nayak — Sat, 27 Feb 2021 22:04:53 -0600

Flanker, a Python package which performs alignment-free clustering of gene flanking sequences in a consistent format, allowing investigation of mobile genetic elements (MGEs) without prior knowledge of their structure. Flanker can be flexibly parameterised to finetune outputs by characterising upstream and downstream regions separately and investigating variable lengths of flanking sequence.

Address of the bookmark: https://github.com/wtmatlock/flanker

GEnView: A phylogeny based comparative genomics software to analyze the genetic environment of genes

Abhi — Tue, 28 Dec 2021 01:49:03 -0600

A phylogeny based comparative genomics software to analyze the genetic environment of genes. The user can select one or several taxa and provide one or several reference protein(s). Genomes and plasmids (based on user choice) will be downloaded from the NCBI Assembly/NR database and searched for the respective gene. Alternatively, custom genomes can be provided. User selected stretches (20kbp by default) of the genes genetic environment are extracted, annotated and aligned between all genomes. The sequences are then visualized, enabling comparison of synteny and gene content.

More at https://pubmed.ncbi.nlm.nih.gov/34951622/

Address of the bookmark: https://github.com/EbmeyerSt/GEnView

2.4 Mb Genome Size for World's Biggest Virus

Jitendra Narayan — Thu, 08 Aug 2013 10:05:37 -0500

The genome size of new discovered Pandoraviruses have roughly twice the size of the record-holding Megavirus genomic code. Interestingly only 6 percent of its genes resembled the genes other organisms. It is assume that it may come from a different origin.

For detail : http://www.sciencemag.org/content/341/6143/281

http://www.npr.org/blogs/health/2013/07/18/203298244/worlds-biggest-virus-may-have-ancient-roots

RCircos: an R package for Circos 2D track plots

Jit — Fri, 20 May 2016 11:01:13 -0500

RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.

More at https://bitbucket.org/henryhzhang/rcircos/src

Address of the bookmark: https://bitbucket.org/henryhzhang/rcircos/src

GeneBreak: a tool to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach

Jit — Sat, 01 Oct 2016 15:15:29 -0500

Development of cancer is driven by somatic alterations, including numerical and structural chromosomal aberrations. Currently, several computational methods are available and are widely applied to detect numerical copy number aberrations (CNAs) of chromosomal segments in tumor genomes. However, there is lack of computational methods that systematically detect structural chromosomal aberrations by virtue of the genomic location of CNA-associated chromosomal breaks and identify genes that appear non-randomly affected by chromosomal breakpoints across (large) series of tumor samples. ‘GeneBreak’ is developed to systematically identify genes recurrently affected by the genomic location of chromosomal CNA-associated breaks by a genome-wide approach, which can be applied to DNA copy number data obtained by array-Comparative Genomic Hybridization (CGH) or by (low-pass) whole genome sequencing (WGS). First, ‘GeneBreak’ collects the genomic locations of chromosomal CNA-associated breaks that were previously pinpointed by the segmentation algorithm that was applied to obtain CNA profiles. Next, a tailored annotation approach for breakpoint-to-gene mapping is implemented. Finally, dedicated cohort-based statistics is incorporated with correction for covariates that influence the probability to be a breakpoint gene. In addition, multiple testing correction is integrated to reveal recurrent breakpoint events. This easy-to-use algorithm, ‘GeneBreak’, is implemented in R (www.cran.r-project.org) and is available from Bioconductor (www.bioconductor.org/packages/release/bioc/html/GeneBreak.html).

Address of the bookmark: http://www.bioconductor.org/packages/release/bioc/html/GeneBreak.html

Understanding liftOver !

Rahul Nayak — Wed, 06 Jun 2018 10:00:20 -0500

LiftOver is a necesary step to bring all genetical analysis to the same reference build. LiftOver can have three use cases:

(1) Convert genome position from one genome assembly to another genome assembly

In most scenarios, we have known genome positions in NCBI build 36 (UCSC hg 18) and hope to lift them over to NCBI build 37 (UCSC hg19).

(2) Convert dbSNP rs number from one build to another

(3) Convert both genome position and dbSNP rs number over different versions

Run:

liftOver input.bed hg18ToHg19.over.chain.gz output.bed unlifted.bed

The outformat is as follow:

Deleted in new:
    Sequence intersects no chains
Partially deleted in new:
    Sequence insufficiently intersects one chain
Split in new:
    Sequence insufficiently intersects multiple chains
Duplicated in new:
    Sequence sufficiently intersects multiple chains
Boundary problem:
    Missing start or end base in an exon

For example:

If you liftOver chr4:6497-6497 from hg19 to GRch38 and it return "deleted in new".

It means chr4:6497-6497 is part of a genomic contig on hg19 that is not anymore mapped on GRch38 because the new assembly is now better built without including this contig.