BOL: Related items

MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly

Abhi — Sat, 08 Jun 2024 16:15:25 -0500

The MetaGraph framework is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as sequence search or differential assembly.

Searcg link https://metagraph.ethz.ch/search

Pre-print https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4

Address of the bookmark: https://metagraph.ethz.ch/

R package for visualising GO enrichment

Jit — Mon, 22 Jul 2013 12:25:09 -0500

An R package that visualizes the GO enrichment results as word clouds and arranges them together with figures of experimental data. This allows us to draw informative summary plots for analyses such as differential expression or clustering, where for each gene list we display its behaviour in the experiment alongside with its GO annotations.

Links @ http://raivokolde.github.io/GOsummaries/

Lab @ http://biit.cs.ut.ee/about/main

RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs

Jit — Sun, 27 Oct 2019 00:57:23 -0500

Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019.

RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:

Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.
Intact ordering and orienting of contigs.
Misassembly correction
GFF lift-over
Structural variant calling with and integrated version of Assemblytics
Confidence scores associated with the grouping, localization, and orientation for each contig.

Address of the bookmark: https://github.com/malonge/RaGOO

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

STELLAR: fast and exact local alignments

Neel — Wed, 29 Aug 2018 16:00:46 -0500

STELLAR is very practical and fast on very long sequences which makes it a suitable new tool for finding local alignments between genomic sequences under the edit distance model. Binaries are freely available for Linux, Windows, and Mac OS X at http://www.seqan.de/projects/stellar.

Address of the bookmark: http://www.seqan.de/apps/stellar/

FLAS: fast and high throughput algorithm for PacBio long read self-correction.

Jit — Sat, 22 Jun 2019 12:16:39 -0500

FLAS, a wrapper algorithm of MECAT, to achieve high throughput long read self-correction while keeping MECAT's fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy.

Address of the bookmark: https://github.com/baoe/flas

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations

Jit — Sun, 15 Dec 2019 10:19:35 -0600

The Docker image is available at https://hub.docker.com/r/biodatageeks/. Supplementary information on benchmarking procedure as well as test data are publicly accessible at the project documentation site http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage. An archival copy of the code and supporting data is also available via the GigaScience database GigaDB

• Project name: SeQuiLa-cov

• Project home page: http://biodatageeks.org/sequila/

• Source code repository: https://github.com/ZSI-Bio/bdg-sequila

• Operating system: Platform independent

• Programming language: Scala

• Other requirements: Docker

• License: Apache License 2.0

Address of the bookmark: https://academic.oup.com/gigascience/article/8/8/giz094/5543653

fastv - detect virus

Jit — Sat, 11 Dec 2021 08:04:10 -0600

fastv is an ultra-fast tool for identification of SARS-CoV-2 and other microbes from sequencing data. It detects microbial sequences from FASTQ data, generates JSON reports and visualizes the result in HTML reports. This tool can be used to detect viral infectious diseases, like COVID-19. This tool supports both short reads (Illumina, BGI, etc.) and long reads (ONT, PacBio, etc.)

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

HELIANO: A fast and accurate tool for detection of Helitron-like elements

LEGE — Tue, 13 Aug 2024 07:16:34 -0500

Helitron-like elements (HLE1 and HLE2) are DNA transposons. They have been found in diverse species and seem to play significant roles in the evolution of host genomes. Although known for over twenty years, Helitron sequences are still challenging to identify. Here, we propose HELIANO (Helitron-like elements annotator) as an efficient solution for detecting Helitron-like elements.

https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae679/7730539?login=true

Address of the bookmark: https://github.com/Zhenlisme/heliano/

Master Thesis: Trans-membrane topology prediction through Markov based decoders

Rahul Agarwal — Wed, 17 Jul 2013 16:16:17 -0500

Abstract:

Background/Motivation:

The dearth of structural information on alpha helical membrane protein (MPs) has hindered thus far the development of reliable knowledge –based potentials that can be used for automatic prediction of trans-membrane (TM) protein structure. While algorithm for identification of TM segments is available, modelling of the domains of alpha helical MPs involves assembling the segments into a bundle. This requires the correct assignment of the buried and lipid-exposed faces of the TM domains.

Results: In a cross validated test on single sequences, our trans-membrane MM, correctly predicts the entire topology for 77% of the sequences in a standard dataset of 86 proteins with supervised topology. These results compare favorably with existing methods.

Source Code: Matlab

Conclusion/Implementation: Here discriminant data mining approach was used to predict the location and orientation of alpha helices in membrane-spanning proteins. It is based on a first order Markov model (MM) with an architecture that corresponds closely to the biological systems. The model is enriched with three types of states for the loop on the cytoplasmic side (outer loop), loop for the non-cytoplasmic side (inner side), and trans-membrane part. The closed association between the biological and Markov states allows us to infer which part of the model architecture are important to capture the information which encodes the membrane topology, and gain a better understanding of the mechanism and constraints involved. Predictor Model was established by various Markov decoder , and assignment of the membrane helix boundaries was apparent.