BOL: Related items

CrocoBLAST: Optimized parallel implementation of local sequence alignment algorithms

Jit — Tue, 25 Jul 2017 05:03:10 -0500

Local sequence alignment is a cornerstone of bioinformatics, allowing to compare the amino-acid sequences of different proteins, or the nucleotide sequences of different pieces of DNA. The Basic Local Alignment Search Tool (BLAST) has revolutionized the field of bioinformatics, and is currently implemented in all free and commercial bioinformatics packages. However, with the advent of Next Generation Sequencing (NGS) and the development of new sequencing techniques, the utility of traditional BLAST implementations is limited. CrocoBLAST combines the accuracy and general applicability of BLAST with computational efficiency, accessibility, and user experience, so that NGS data can be analyzed efficiently even when only modest computational resources are available.

https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST

Address of the bookmark: https://webchem.ncbr.muni.cz/Platform/App/CrocoBLAST

Scripts for the analysis of HGT in genome sequence data.

Jit — Wed, 29 Nov 2017 16:44:10 -0600

Scripts for the analysis of HGT in genome sequence data

Address of the bookmark: https://github.com/reubwn/hgt

Ancestral sequence reconstruction steps !

Surabhi Chaudhary — Fri, 18 May 2018 08:28:26 -0500

Ancestral sequence reconstruction (ASR) – also known as ancestral gene/sequence reconstruction/resurrection – is a technique used in the study of molecular evolution. The method consists of the synthesis of an ancestral gene and expression of the corresponding ancestral protein. The idea of protein 'resurrection' was suggested in 1963 by Pauling and Zuckerkandl. Some early efforts were made in the eighties-nineties, led by the laboratory of Steven A. Benner, showing the potential of this technique – one that only started to be fulfilled in the post-genomic era. Thanks to the improvement of algorithms and of better sequencing and synthesis techniques, the method was developed further in the early 2000s to allow the resurrection of a greater variety of and much more ancient genes. Over the last decade, ancestral protein resurrection has developed as a strategy to reveal the mechanisms and dynamics of protein evolution.

BEAST is the best way to predict the ancestral structure. but, I suggest following steps?

1- Alignments "Mafft - http://mafft.cbrc.jp/alignment/software/source.html"

mafft --maxiterate 1000 --reorder --thread 24 --genafpair Dataset.fasta > Dataset_Alig.fasta

2- Your dataset has a good phylogenetic signal, is possible to perform with Tree-Puzzle "http://www.tree-puzzle.de";

3 - This dataset which the saturation index, I perform with "http://dambe.bio.uottawa.ca/dambe.asp";

4- Has evidence of possible recombination in your dataset, the evaluate if this presence or absence, because this may to influence the grouping of clades, I perform with

---recombination

4.1- Phi-test, implemented in SplitTree4"http://www.splitstree.org", (.nex file)

4.2- GARD deployed in webserver in the DataMonkey "http://www.datamonkey.org/" - turning to the amino acid seaview -> view proteins -> save as ...) Ideally do a tree-based groups.

4.3- RDP4 for download and installation on Windows in "http://web.cbio.uct.ac.za/~darren/rdp.html"

4.4- Hyphy (Mac, Windows, Linux) in "http://hyphy.org/w/index.php/Download"

4.5- Path-o-Gen (temporal structure of a tree input file -> arquivo.tre)

These steps above, I call of pre-processing to inferences phylogenetic...

5- Perform phylogenetic tree, used Bayesian Inference with Molecular Clock, but is necessary Clock Testing:

- This step is performed with program Beast (Beauti, Beast and TreeAnnotator), and Tracer_v1.5 more FigTree to inspection.

- Tutorials: http://beast.bio.ed.ac.uk/tutorials

- Downloads: http://beast.bio.ed.ac.uk/downloads

SDA: Long-read sequence and assembly of segmental duplications

Jit — Tue, 05 Mar 2019 10:00:57 -0600

Segmental Duplication Assembler (SDA; https://github.com/mvollger/SDA) constructs graphs in which paralogous sequence variants define the nodes and long-read sequences provide attraction and repulsion edges, enabling the partition and assembly of long reads corresponding to distinct paralogs.

https://github.com/mvollger/SDA

Address of the bookmark: https://www.nature.com/articles/s41592-018-0236-3

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

Complete genome sequence of Wuhan seafood market pneumonia virus is out !

Jit — Fri, 31 Jan 2020 02:36:59 -0600

Wuhan-Hu-1 claimed at least 40 lives and infected at least 1300 others in China. Cases are now being reported from Thailand, Singapore, Malaysia, South Korea, Japan, Vietnam, Nepal, France, Australia and even as far as the US. On Jan 10 2020, while news of the first fatality was barely trickling in, the 29,903 letters constituting the viral genome from an affected individual in Wuhan had already been elucidated (even though a few corrections were made subsequently). All the viral genome sequences from affected individuals are very very close to each other. Several are identical and none has more than 5 differences (99.983% similarity). This strongly suggests that transmission into humans came from a single pointed source and happened very recently, between Sep-Dec 2019.

Check out the detail at https://www.ncbi.nlm.nih.gov/nuccore/MN908947

China’s BGI says it can sequence a genome for just $100

Neel — Sat, 29 Feb 2020 04:49:43 -0600

Using technology originally acquired in the US, the Chinese gene giant BGI Group says it will make genome sequencing cheaper than ever, breaking the $100 barrier for the first time.

The Shenzhen company says the low cost will be possible with an “extreme” DNA sequencing system it plans to offer that is capable of decoding the genomes of 100,000 people a year.

Ref: https://www.technologyreview.com/s/615289/china-bgi-100-dollar-genome/

MMseqs2: ultra fast and sensitive sequence search and clustering suite

Manisha Mishra — Mon, 18 Jan 2021 10:47:56 -0600

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

Address of the bookmark: https://github.com/soedinglab/MMseqs2

UniAligner: a parameter-free framework for fast sequence alignment

Abhi — Fri, 08 Mar 2024 23:36:12 -0600

UniAligner (formerly, TandemAligner) is the first parameter-free algorithm for sequence alignment that introduces a sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. Classical alignment approaches, such as the Smith-Waterman algorithm, that work well for most sequences, fail to construct biologically adequate alignments of extra-long tandem repeats (ETRs), such as human centromeres and immunoglobulin loci. This limitation was overlooked in the previous studies since the sequences of the centromeres and other ETRs across multiple genomes only became available recently.

More at https://www.nature.com/articles/s41592-023-01970-4

Address of the bookmark: https://github.com/seryrzu/unialigner

NGS Tutorial

Jit — Mon, 05 Sep 2016 09:50:46 -0500

These tutorials are written for hundreds of bioinformaticians trying to cope with large volume of next-generation sequencing (NGS) data. NGS technologies brought a dramatic shift in the world of sequencing. Merely five years back, genome sequencing of higher eukaryotes used to be very expensive endeavor. To get a genome of interest sequenced, hundreds of scientists had to raise funds together by writing a joint white-paper and petitioning to various government agencies. The tasks of sequencing and assembly were handled by dedicated sequencing facilities, of which only a few existed around the globe. Naturally, the capacities at those sequencing facilities were significantly constrained from high volume of requests

Address of the bookmark: http://www.homolog.us/Tutorials/index.php