BOL: Related items

RNA Bioinformatics and High Throughput Analysis Jena

Sat, 09 Nov 2013 20:03:56 -0600

Research Topics:

High Throughput Sequencing Analysis
Comparative Genomics
Identification and Annotation of Non-coding RNAs
Bioinformatic Analysis and System Biology of Viruses
Coevolution of Proteins and RNAs
Algorithmic Bioinformatics
Phylogenetic Analysis

http://www.rna.uni-jena.de/index.php

Bio-Rad Acquires GnuBIO

Rahul Agarwal — Sat, 19 Apr 2014 10:36:36 -0500

http://www.businesswire.com/news/home/20140411005331/en/Bio-Rad-Acquires-GnuBIO-Developer-Droplet-Based-DNA-Sequencing#.U1KXnPm1b8o

Deadly Human Pathogen Cryptococcus Sequenced

Rahul Agarwal — Fri, 25 Apr 2014 11:02:21 -0500

"Now, researchers have sequenced the entire genome and all the RNA products of the most important pathogenic lineage of Cryptococcus neoformans, a strain called H99. The results, which appear in PLOS Genetics, also describe a number of genetic changes that can occur after laboratory handling of H99 that make it more susceptible to stress, hamper its ability to sexually reproduce and render it less virulent."

Source:

http://www.biosciencetechnology.com/news/2014/04/deadly-human-pathogen-cryptococcus-fully-sequenced

Paper:

http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1004292

Drawback of Exome Sequencing

Rahul Agarwal — Mon, 02 Jun 2014 05:46:43 -0500

Dr Eric Londin, Assistant Professor, Thomas Jefferson University, USA, stated that analysis of 44 exome datasets from four different testing kits showed that they missed a high proportion of clinically relevant regions in the 56 ACMG genes. "At least one gene in each exome method was missing more than 40 percent of disease-causing genetic variants, and we found that the worst-performing method missed more than 90 percent of such variants in four of the 56 genes," he says.

Source: http://www.eurekalert.org/pub_releases/2014-05/esoh-pco052914.php

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads

Rahul Agarwal — Mon, 06 Jul 2015 08:46:53 -0500

GraphMap is a novel mapper targeted at aligning long, error-prone third-generation sequencing data.
It is designed to handle Oxford Nanopore MinION 1d and 2d reads with very high sensitivity and accuracy, and also presents a significant improvement over the state-of-the-art for PacBio read mappers.

GraphMap was also designed for ease-of-use: the default parameters can handle a wide range of read lengths and error profiles, including: Illumina, PacBio and Oxford Nanopore.
This is an especially important feature for technologies where the error rates and error profiles can vary widely across, or even within, sequencing runs.

http://biorxiv.org/content/early/2015/06/10/020719

Address of the bookmark: https://github.com/isovic/graphmap

CovCal: Coverage / Read Count Calculator

Jit — Wed, 15 Jun 2016 18:08:13 -0500

Coverage / Read Count Calculator

Calculate how much sequencing you need to hit a target depth of coverage (or vice versa).

Instructions: set the read length/configuration and genome size, then select what you want to calculate.

Written by Stephen Turner, based on the Lander-Waterman formula, inspired by a similar calculator written by James Hadfield. Coverage is calculated as C=LN/G and reads as N=CG/L where C = Coverage (X),L = Read length (bp), G = Haploid genome size (bp), and N = Number of reads. Source code on GitHub.

Address of the bookmark: http://apps.bioconnector.virginia.edu/covcalc/

Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator

Jit — Wed, 24 May 2017 08:41:41 -0500

Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file.

Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.

Address of the bookmark: https://sourceforge.net/projects/biogrinder/files/biogrinder/

LRSDAY: Long-read Sequencing Data Analysis for Yeasts

Poonam Mahapatra — Mon, 26 Aug 2019 18:07:33 -0500

Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast, Saccharomyces cerevisiae, has many isolates currently being sequenced with long reads.

Address of the bookmark: https://github.com/yjx1217/LRSDAY

Choosing the Right NGS Sequencing Instrument for Your Study

Neel — Wed, 15 Jun 2022 00:37:29 -0500

The right sequencing instrument for your study depends on your project goal. Setting aside turnaround time and price, it essentially comes down to the numbers of reads and read length you need for your experiment. Below, we've described and compared metrics for each of the instruments available. If you’re new to high-throughput sequencing and have questions about how you should design your sequencing run, fill out our free consultation form and we'll get in touch with you to help.

More at https://genohub.com/ngs-instrument-guide/

Address of the bookmark: https://genohub.com/ngs-instrument-guide/

Structure of Binary files used for storing sequencing data-bam and sff

Rahul Agarwal — Sun, 11 Aug 2013 14:29:49 -0500

Many times bioinformatician needs to parse binary files like bam and sff. Advantage of binary files is that they occupy less space in memory with maximum information content.

Link for those who looking for structure of Bam and sff file:

Bam:

http://samtools.sourceforge.net/SAMv1.pdf (from page 12)

sff file (for Ion torrent and 454 files):

http://www.ncbi.nlm.nih.gov/Traces/trace.cgi?cmd=show&f=formats&m=doc&s=format#sff

Binary file Editor and Viewer:

http://mh-nexus.de/en/hxd/