BOL: Related items

NanoPack: visualizing and processing long-read sequencing data

Jit — Tue, 25 Dec 2018 21:20:50 -0600

The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

Address of the bookmark: https://github.com/wdecoster/nanopack

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

mosdepth: fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing

Jit — Wed, 13 Nov 2019 22:20:19 -0600

mosdepth can output:

per-base depth about 2x as fast samtools depth--about 25 minutes of CPU time for a 30X genome.
mean per-window depth given a window size--as would be used for CNV calling.
the mean per-region given a BED file of regions.
a distribution of proportion of bases covered at or above a given threshold for each chromosome and genome-wide.
quantized output that merges adjacent bases as long as they fall in the same coverage bins e.g. (10-20)
threshold output to indicate how many bases in each region are covered at the given thresholds.
A summary of mean depths per chromosome and within specified regions per chromosome.

Address of the bookmark: https://github.com/brentp/mosdepth

FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads

Jit — Tue, 28 Jan 2020 03:27:33 -0600

FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.

http://bioinfo.ut.ee/FastGT/

https://github.com/bioinfo-ut/GenomeTester4/

Address of the bookmark: http://bioinfo.ut.ee/FastGT/

Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Jit — Thu, 28 May 2020 21:57:03 -0500

Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

Smudgeplot: Inference of ploidy and heterozygosity structure using whole genome sequencing data

Neel — Fri, 25 Feb 2022 04:42:09 -0600

This tool extracts heterozygous kmer pairs from kmer count databases and performs gymnastics with them. We are able to disentangle genome structure by comparing the sum of kmer pair coverages (CovA + CovB) to their relative coverage (CovB / (CovA + CovB)). Such an approach also allows us to analyze obscure genomes with duplications, various ploidy levels, etc.

Smudgeplots are computed from raw or even better from trimmed reads and show the haplotype structure using heterozygous kmer pairs. For example:

Address of the bookmark: https://github.com/KamilSJaron/smudgeplot

Illumina Smartphone Chip !!!

Robert M Willioms — Tue, 30 Dec 2014 23:19:54 -0600

Illumina, the company that claims it brought human genome sequencing down to $1000 prices, has now turned its attention to a consumer product - a chip that you can plug into your smartphone and have it read your genetic information.

The biggest challenge ahead of Illumina is simplifying the process of genetic sequencing. Currently, Illumina’s DNA sequencers are gigantic machines that use techinques like colorimetry to work, but while the core technology is computational, it takes some 30 steps to extract genetic data and run it through. This process will likely have to be hugely simplified on mobile devices, given the fact that some studies require extracting 10 mililiters of blood. Illumina researchers are also working on finding the optimal technology for this on-chip DNA sequencing - be it electrical, optical, or other.

Illumina is one of the most prominent names in genetics, often said to be the Intel of genetic sequencing, as just like Intel it provides the algorithms, the processing brain that runs a DNA reading task.

In other recent smartphone-related biotech news, drug company Pfizer launched its REMOTE project, a new type of clinical trial that does not require going to a hospital for checks - targeted at patients with overactive bladder problems, the FDA-approved REMOTE project allowed to gather data from patients from over 10 states remotely, via mobile devices.

This is indeed the Illumina answer to Apple's Health app, HealthBook, Google HealthFit.

Trimmomatic: A flexible read trimming tool for Illumina NGS data

Jit — Fri, 15 Apr 2016 05:58:53 -0500

Paired End:

java -jar trimmomatic-0.35.jar PE -phred33 input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36

This will perform the following:

Remove adapters (ILLUMINACLIP:TruSeq3-PE.fa:2:30:10)
Remove leading low quality or N bases (below quality 3) (LEADING:3)
Remove trailing low quality or N bases (below quality 3) (TRAILING:3)
Scan the read with a 4-base wide sliding window, cutting when the average quality per base drops below 15 (SLIDINGWINDOW:4:15)
Drop reads below the 36 bases long (MINLEN:36)

More at http://www.usadellab.org/cms/?page=trimmomatic

Address of the bookmark: http://www.usadellab.org/cms/?page=trimmomatic

QuorUM: An Error Corrector for Illumina Reads

Jit — Wed, 08 Nov 2017 11:40:41 -0600

Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.

QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821

Illumina to Acquire Pacific Biosciences for Approximately $1.2 Billion !

Rahul Nayak — Fri, 02 Nov 2018 09:57:48 -0500

Illumina and Pacific Biosciences announced they have signed an agreement for Illumina to acquire Pacific Biosciences at a price of $8.00 per Pacific Biosciences share in an all-cash transaction.

The agreement has been approved by the board of directors of Illumina and Pacific Biosciences. The acquisition complements Illumina sequencing solutions with accurate long-read sequencing capabilities to answer a set of complex genomic questions. While Illumina's accurate and economic short-read sequencing platforms address the majority of sequencing applications optimally, select applications, such as de novo sequencing and sequencing of highly homologous regions of genomes, are better addressed with accurate long-reads.

Reference https://www.pacb.com/press_releases/illumina-to-acquire-pacific-biosciences-for-approximately-1-2-billion-broadening-access-to-long-read-sequencing-and-accelerating-scientific-discovery/