BOL: Related items

SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins

BioStar — Mon, 17 Aug 2020 05:25:10 -0500

SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:

Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
Co-assembly of a large number of metagenomes via merging of individual metagenomes
Includes binning and bin checking, for retrieving individual genomes
The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

JUDI: Just Do It

Jit — Mon, 06 Sep 2021 02:44:35 -0500

judi comes from the idea of bringing the power and efficiency of doit to execute any kind of task under many combinations of parameter settings.

https://github.com/ncbi/JUDI

Address of the bookmark: https://github.com/ncbi/JUDI

PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome skimming data

Abhi — Wed, 06 Sep 2023 00:14:28 -0500

Phylogenomic Analysis Pipeline for Herbarium Specimens

What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs (NTS+ETS+18S+ITS1+5.8S+ITS2+28S), alignments of gene and intergenic regions, and a species tree. It is designed to be a high throughput program dealing with lower quality data. Examples include low-coverage (5x cpDNA) plastome phylogeny, recycling plastid genes from target enrichment data, retrieving low-copy nuclear genes from medium coverage (5x nucDNA) genome skimming.

License: GNU General Public License

Citation:

Cai, Liming, Hongrui Zhang, and Charles C. Davis. 2022. PhyloHerb: A high‐throughput phylogenomic pipeline for processing genome‐skimming data. Applications in Plant Sciences 10(3): 1–9. https://doi.org/10.1002/aps3.11475

Address of the bookmark: https://github.com/lmcai/PhyloHerb/

iMAGine - in silico MetAGenomics pipeline

BioStar — Sat, 06 Jul 2024 04:32:18 -0500

iMAGine is a metagenomic workflow which includes filtering, assembling, and binning.

This workflow includes the following tools which are needed to be installed in the system.

Address of the bookmark: https://github.com/avishekdutta14/iMAGine

PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool

Jit — Fri, 01 Dec 2017 04:10:54 -0600

PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
Reduces the processing time of sequences comparisons while providing highest quality results,
Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/

HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies

Jit — Tue, 15 May 2018 07:35:26 -0500

HapCUT2 is a maximum-likelihood-based tool for assembling haplotypes from DNA sequence reads, designed to "just work" with excellent speed and accuracy. We found that previously described haplotype assembly methods are specialized for specific read technologies or protocols, with slow or inaccurate performance on others. With this in mind, HapCUT2 is designed for speed and accuracy across diverse sequencing technologies, including but not limited to: NGS short reads (Illumina HiSeq) clone-based sequencing (Fosmid or BAC clones) SMRT reads (PacBio) Oxford Nanopore reads 10X Genomics Linked-Reads proximity-ligation (Hi-C) reads high-coverage sequencing (>40x coverage-per-SNP) using above technologies combinations of the above technologies (e.g. scaffold long reads with Hi-C reads) See below for specific examples of command line options and best practices for some of these technologies. NOTE: At this time HapCUT2 is for diploid organisms only. VCF input should contain diploid variants. If you use HapCUT2 in your research, please cite: Edge, P., Bafna, V. & Bansal, V. HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies. Genome Res. gr.213462.116 (2016). doi:10.1101/gr.213462.116

Address of the bookmark: https://github.com/vibansal/HapCUT2

P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads

BioStar — Fri, 07 Sep 2018 05:19:06 -0500

P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance, PEP_scaffolder ) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance, circRNA).

Address of the bookmark: http://www.fishbrowser.org/software/P_RNA_scaffolder/#

Artificial intelligence is more accurate than doctors in diagnosing breast cancer

BioStar — Wed, 01 Jan 2020 22:12:34 -0600

Artificial intelligence is more accurate than doctors in diagnosing breast cancer from mammograms, a study in the journal Nature suggests.

An international team, including researchers from Google Health and Imperial College London, designed and trained a computer model on X-ray images from nearly 29,000 women.

The algorithm outperformed six radiologists in reading mammograms.

AI was still as good as two doctors working together.

Unlike humans, AI is tireless. Experts say it could improve detection. Read More: https://www.bbc.com/news/health-50857759

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

BioStar — Fri, 27 Mar 2020 22:49:31 -0500

HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.

More at https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3

Address of the bookmark: https://github.com/marbl/canu

Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data

Jit — Thu, 11 Feb 2021 21:39:05 -0600

Ktrim is written in C++ for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file ktrim under bin/ directory compiled using g++ v4.8.5 and linked with libz v1.2.7 for Linux x86_64 system. If you could not run it (which is usually caused by low version of libc++ or libz library) or you want to build a version optimized for your system, you can re-compile the programs:

user@linux$ make clean && make

Address of the bookmark: https://github.com/hellosunking/Ktrim