BOL: Related items

COSINE: non-seeding method for mapping long noisy sequences

Jit — Fri, 26 Oct 2018 00:41:59 -0500

Third generation sequencing (TGS) are highly promising technologies but the long and noisy reads from TGS are difficult to align using existing algorithms. Here, we present COSINE, a conceptually new method designed specifically for aligning long reads contaminated by a high level of errors.

Address of the bookmark: https://github.com/SUwonglab/COSINE

Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.

Jit — Tue, 18 Jun 2019 05:33:04 -0500

Cogent is a tool that identifies gene families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check assemblies for the presence of these known coding sequences.

Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on Iso-Seq data and in cases where there is no reference genome or the ref genome is highly incomplete.

See a recent presentation on Cogent being applied to the Cuttlefish Iso-Seq data.

Cogent preliminary draft paper (updated 2016Dec version), Supplementary

Please see wiki for details on usage.

Address of the bookmark: https://github.com/Magdoll/Cogent

Tiara: deep learning-based classification system for eukaryotic sequences

Rahul Nayak — Mon, 14 Mar 2022 23:02:11 -0500

With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding of eukaryotic diversity.

Address of the bookmark: https://academic.oup.com/bioinformatics/article/38/2/344/6375939

Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences

LEGE — Sun, 31 Aug 2025 06:30:16 -0500

Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.

Address of the bookmark: https://github.com/MGXlab/Jaeger

sockeye

Jit — Fri, 17 Feb 2017 08:51:16 -0600

This sockeye software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3

Circoletto: visualizing sequence similarity with Circos

Jit — Fri, 09 Feb 2018 10:23:40 -0600

Circoletto, an online visualization tool based on Circos, which provides a fast, aesthetically pleasing and informative overview of sequence similarity search results.

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

IRscope: an online program to visualize the junction sites of chloroplast genomes

Neel — Wed, 25 Nov 2020 19:44:46 -0600

eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.

Address of the bookmark: https://sites.google.com/g.hmc.edu/empress/home

Kraken: ultrafast metagenomic sequence classification using exact alignments

Jit — Mon, 27 Jun 2016 11:01:44 -0500

Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of k-mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at http://ccb.jhu.edu/software/kraken/.

Krona

https://sourceforge.net/p/krona/home/krona/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/

BLAST options, setting and defaults

Jit — Mon, 10 Dec 2018 08:29:37 -0600

BLAST stands for Basic Local Alignment Search Tool and was developed by Altschul et al. (1990) and significantly improved by Altschul et al. (1997). It is a very fast search algorithm that is used to separately search protein or DNA databases. BLAST is best used for sequence similarity searching, rather than for motif searching. For searches using a query sequence of fewer than twenty residues, PatMatch is the best choice. Another sequence alignment tool that may yield different results from BLAST, and may be useful for motif searching, is FASTA. To search nonplant datasets, try NCGR BLAST or NCBI BLAST.

A fairly complete on-line guide to BLAST searching can be found at the NCBI BLAST Help Manual. For a theoretical overview of BLAST, see the NCBI BLAST Course. Additional information can be found in the BLAST 2.0 Release Notes

	BLASTN	BLASTP	BLASTX	TBLASTN	TBLASTX	PSIBLAST
Gap opening penalty: cost to open a gap [integer]	default = 5	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 11 limited values are supported	default = 5
Gap extension penalty: cost to extend a gap [integer]	default = 2	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 1 a 0 in this field means to use the default	default = 2
Nucleic match: reward for a match in the BLAST portion of run [integer]	default = 1	n/a	n/a	n/a	n/a	default = 1
Nucleic mismatch: penalty for a mismatch in the blast portion of run [integer]	default = -3	n/a	n/a	n/a	n/a	default = -3
Expectation value: (E) [real]	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0	default = 10.0
Word size: the size of the initial word that must be matched between the database and the query sequence	default = 11	default = 3	default = 3	default = 3	default = 3	default = 11
Max scores: Number of one-line descriptions (V) [Integer]	default = 25	default = 25	default = 25	default = 25	default = 25	default = 25
Max alignments: number of alignments to show (B) [integer]	default = 15	default = 15	default = 15	default = 15	default = 15	default = 15
Query filter: filter applied to the query sequence	default = DUST	default = SEG	default = SEG	default = SEG	default = SEG	default = DUST
Query genetic code: genetic code to be used in BLASTX translation of the query	n/a	n/a	default = universal	default = universal	default = universal	n/a
Matrix: substitution matrix to be used for amino acid comparisons	no default	default = blosum62	default = blosum62	default = blosum62	default = blosum62	no default

Supported and Suggested Values for Gap Open and Extension in BLASTP, BLASTX, TBLASTN, and TBLASTX

Gaps Open	Gap Extension
10	1
10	2
11	1
8	2
9	2

Address of the bookmark: https://www.arabidopsis.org/Blast/BLASToptions.jsp

Is reference genome necessary for gene expression study in transcriptome sequencing or for variant discovery in genome sequencing?

Rahul Agarwal — Wed, 17 Jul 2013 15:25:09 -0500

Like in case of plant genomes where nature of genome is too complex and huge in size to accomplish complete de novo assembly by current sequencing technology. What would be alternate solution? Can we live in reference free world?