BOL: Related items

ngs-bits - Short-read sequencing tools

Neel — Thu, 16 Jan 2020 23:14:00 -0600

Binaries of ngs-bits are available via Bioconda. Alternatively, ngs-bits can be built from sources:

Binaries for Linux/macOS
From sources for Linux/macOS
From sources for Windows

Address of the bookmark: https://github.com/imgag/ngs-bits

SimLoRD: A read simulator for third generation sequencing reads

Aaryan Lokwani — Wed, 22 Aug 2018 10:40:27 -0500

SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.

Reads are simulated from both strands of a provided or randomly generated reference sequence.

The reference can be read from a FASTA file or randomly generated with a given GC content. It can consist of several chromosomes, whose structure is respected when drawing reads. (Simulation of genome rearrangements may be incorporated at a later stage.)
The read lengths can be determined in four ways: drawing from a log-normal distribution (typical for genomic DNA), sampling from an existing FASTQ file (typical for RNA), sampling from a a text file with integers (RNA), or using a fixed length
Quality values and number of passes depend on fragment length.
Provided subread error probabilities are modified according to number of passes
Outputs reads in FASTQ format and alignments in SAM format

Address of the bookmark: https://bitbucket.org/genomeinformatics/simlord/

Does anyone have Nanopore latest updates?

Poonam Mahapatra — Mon, 12 Aug 2013 12:19:29 -0500

There was a lot of buzz about Oxford Nanopore Technologies® is developing the GridION™ system and miniaturised MinION™ device. These are a new generation of electronic molecular analysis system for use in scientific research, personalised medicine, crop science, security/defence and more. The platform technology uses nanopores to analyse single molecules including DNA/RNA and proteins. With a broad patent portfolio, the Oxford Nanopore pipeline includes biological nanopores and solid-state nanopores.

Is this available, or still under trial mode?

https://www.nanoporetech.com/

https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system

GenomeScope: open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads

Jit — Fri, 21 Oct 2016 05:46:43 -0500

Summary: GenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates. Availability and Implementation: http://qb.cshl.edu/genomescope/, https://github.com/schatzlab/genomescope.git

Address of the bookmark: http://qb.cshl.edu/genomescope/

1mb long DNA with Nanopore technology

Jit — Tue, 19 Dec 2017 18:49:28 -0600

The first continuous DNA read of more than a million bases (>1Mb) has been achieved, using Oxford Nanopore sequencing technology. Congratulations to Martin Smith and collaborators! Read more: http://bit.ly/2j5TNCO

Flye: Fast and accurate de novo assembler for single molecule sequencing reads

BioJoker — Tue, 02 Apr 2019 21:54:55 -0500

Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.

Address of the bookmark: https://github.com/fenderglass/Flye

MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization

Jit — Fri, 24 Jan 2020 04:09:15 -0600

MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from https://github.com/linzhi2013/MitoZ.

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data

Jit — Thu, 31 May 2018 09:35:23 -0500

BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes. The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC. https://github.com/lh3/bfc

Address of the bookmark: https://github.com/lh3/bfc

ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies

Neel — Tue, 26 Apr 2016 03:38:43 -0500

Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.

More at http://www.ncbi.nlm.nih.gov/pubmed/23303509

Address of the bookmark: http://sc932.github.io/ALE/about.html

Live Webinar on RNA-Seq Data Analysis on 9 Nov 2016

Strand — Wed, 19 Oct 2016 05:25:27 -0500

Live Webinar on RNA-Seq Data Analysis

Abstract: Strand NGS supports an extensive workflow for the analysis and visualization of RNA-Seq data. The workflow includes Transcriptome / Genome alignment, Differential expression analysis with Statistical approach and Splicing events detection. Strand NGS also supports novel discovery like identification of novel genes, exons and Novel splice junctions, alongside it can also detect gene fusion events. Further downstream analysis such as GO and pathway analysis can be performed on the set of interesting genes. The product has an option to create pipelines for time consuming jobs which automates analysis and leaves more time for end data interpretation. This webinar will give an overview of the features in the RNA-Seq data analysis workflow in Strand NGS and also highlights on parameters within each feature that can be optimized depending on datasets and analysis needs.

Speaker: Mr. Sugandan Sivamani, Senior Application Scientist, Strand Life Sciences

Date: 9th Nov, Session 1 for SAPK/ APFO: 2:30 PM IST Date: 9th Nov, Session 2 for AFO/ EMEA: 9:00 AM PST