BOL: Related items

poRe: an R package for the visualization and analysis of nanopore sequencing data

Jit — Thu, 23 Nov 2017 09:55:57 -0600

Motivation: The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.

Results: Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.

Availability and implementation: poRe is released as a package for R at http://sourceforge.net/projects/rpore/ . A tutorial and further information are available at https://sourceforge.net/p/rpore/wiki/Home/

Contact:mick.watson@roslin.ed.ac.uk

Address of the bookmark: https://academic.oup.com/bioinformatics/article/31/1/114/2365693

TelomereHunter

Jit — Fri, 02 Feb 2018 04:23:59 -0600

TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.

TelomereHunter is available for download at the following address: https://pypi.python.org/pypi/telomerehunter/

Address of the bookmark: http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html

HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads

Rahul Nayak — Tue, 08 May 2018 04:27:22 -0500

HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs [Sirén et al. 2014], we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM).

more at https://ccb.jhu.edu/software/hisat2/index.shtml

Address of the bookmark: https://github.com/infphilo/hisat2

BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,

Jit — Wed, 23 May 2018 06:54:32 -0500

BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.

Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The “target.fasta.sa” is the suffix array from “target.fasta” generated by sawriter.

blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15

the output format option “-m 4″ generate the alignment coordinate. Not fully documented, but I can explain that to you.

I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.

Address of the bookmark: http://bix.ucsd.edu/projects/blasr/

ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data

Rahul Nayak — Tue, 03 Jul 2018 04:14:52 -0500

ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.

Address of the bookmark: https://github.com/bcgsc/ChopStitch

NanoPack: visualizing and processing long-read sequencing data

Jit — Fri, 10 Aug 2018 18:41:34 -0500

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.

https://academic.oup.com/bioinformatics/article/34/15/2666/4934939

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

d2Tools: The toolbox for counting the frequency of k-tuple from sequencing datasets and calculate the dissimilarity

Jit — Thu, 20 Sep 2018 08:38:29 -0500

d2Tools are the toolbox for counting the frequency of K-tuple from sequencing datasets and then calculating the pairwise dissimilarity matrix between samples with the d2-style(d2/d2*/d2S representing d2/d2Star/d2shepp, respectively) measures. Hao, Dai, Eucliean, Mahattan, and Chebyshev distance measures are also included in d2Tools.

Manual at https://code.google.com/archive/p/d2-tools/wikis/d2ToolMannual.wiki

Address of the bookmark: https://code.google.com/archive/p/d2-tools/

NGS Platforms launched by BGI’s MGI Tech

Jit — Thu, 10 Jan 2019 04:42:06 -0600

MGI Tech Co., Ltd. (MGI), a subsidiary of BGI Group, is committed to enabling effective and affordable healthcare solutions for all. Based on its proprietary technology, MGI produces sequencing devices, equipment, consumables and reagents to support life science research, medicine and healthcare. MGI's multi-omics platforms include genetic sequencing, mass spectrometry and medical imaging. Providing real-time, comprehensive, life-long solutions, its mission is to develop and promote advanced life science tools for future healthcare.

MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to $5 per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.

In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for $1 million.

The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.

Powered by DNBseq™, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.

SOURCE MGI

https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/

http://en.mgitech.cn/

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

PhD position in Translational Medicine

Sat, 15 Feb 2020 06:07:19 -0600

https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/wissenschaftliche-r-mitarbeiter-in/phd-position-translational-medicine-129981.html?suid=1b510358c7578e8f75cf04a464fc21a404a574ca

Essential experience / qualifications:
Master / Diploma in Biology, Biochemistry, Molecular Medicine or similar; solid knowledge of molecular and cell biological techniques; good English knowledge

Applications:
Please send your application (including CV, letter of motivation, contact information of two references, and list of publication) by 13.03.2020 at the latest to:

Universitätsklinikum Erlangen
Chirurgische Klinik
Translational Research Center
Prof. Dr. rer. nat. Michael Stürzl
Schwabachanlage 12
91054 Erlangen
E-Mail: michael.stuerzl@uk-erlangen.de