BOL: Related items

Quick next generation sequencing (NGS) terms definition

Neel — Fri, 09 Jun 2017 04:52:26 -0500

fragment size: the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [δmin,δmax]. Most (>90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.

concordant reads: a read pair is called concordant if they can be mapped to the reference genome as “expected”: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.

discordant reads: briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.

split reads: a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).

read depth: number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that “cover” each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).

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/

Ranbow: a haplotype assembler for polyploid genomes

Jit — Fri, 01 Jun 2018 07:21:54 -0500

Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function: ranbow hap: for haplotyping ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads ranbow phylo: for the phylogenetic analysis

Address of the bookmark: https://www.molgen.mpg.de/ranbow

Installing Salmon for Trinity !

Rahul Nayak — Tue, 03 Jul 2018 09:02:29 -0500

➜ trinityrnaseq-Trinity-v2.6.6 git:(master) ✗ conda install salmon
Solving environment: done

## Package Plan ##

environment location: /home/urbe/anaconda3

added / updated specs:
- salmon

The following packages will be downloaded:

package | build
---------------------------|-----------------
boost-1.64.0 | py36_4 331 KB conda-forge
jemalloc-5.1.0 | hfc679d8_0 8.2 MB conda-forge
boost-cpp-1.64.0 | 1 17.8 MB conda-forge
salmon-0.10.2 | 1 3.7 MB bioconda
conda-4.5.5 | py36_0 624 KB conda-forge
tbb-2018_20171205 | 0 1.2 MB conda-forge
------------------------------------------------------------
Total: 31.8 MB

The following NEW packages will be INSTALLED:

boost: 1.64.0-py36_4 conda-forge
boost-cpp: 1.64.0-1 conda-forge
jemalloc: 5.1.0-hfc679d8_0 conda-forge
salmon: 0.10.2-1 bioconda
tbb: 2018_20171205-0 conda-forge

The following packages will be UPDATED:

conda: 4.5.4-py36_0 conda-forge --> 4.5.5-py36_0 conda-forge

Proceed ([y]/n)? y

Downloading and Extracting Packages
boost-1.64.0 | 331 KB | ####################################################################################################################################### | 100%
jemalloc-5.1.0 | 8.2 MB | ####################################################################################################################################### | 100%
boost-cpp-1.64.0 | 17.8 MB | ####################################################################################################################################### | 100%
salmon-0.10.2 | 3.7 MB | ####################################################################################################################################### | 100%
conda-4.5.5 | 624 KB | ####################################################################################################################################### | 100%
tbb-2018_20171205 | 1.2 MB | ####################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

List of non-commercial NGS genotype-calling software

Jit — Thu, 09 Aug 2018 04:21:32 -0500

Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.

A list of programs for genotype and SNP calling :

SOAP2 http://soap.genomics.org.cn/index.html

Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)

realSFS http://128.32.118.212/thorfinn/realSFS/

Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation

Samtools http://samtools.sourceforge.net/

Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)

GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)

Beagle http://faculty.washington.edu/browning/beagle/beagle.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling

IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map

QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL

Multi-sample LD ‘Feasible’ genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The ‘feasible’ genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)

MaCH http://genome.sph.umich.edu/wiki/Thunder

Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information

AMStat: display statistics of large sequence files from next generation sequencing projects

Neel — Fri, 09 Nov 2018 13:34:56 -0600

SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to SAM/BAM files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.

Address of the bookmark: http://samstat.sourceforge.net/

Introduction to Bioinformatics

eliabrodsky — Wed, 05 Jun 2019 14:58:11 -0500

Introduction to bioinformatics is a course for biologists and clinicians that would like to learn more about the way bioinformatics is used in healthcare, biotech and pharmaceuitcal industry as well as basic research. The course covers many of the topics transformed by the emergence of big data and computational technologies. To learn more about the course, visit: https://edu.t-bio.info/course/introduction-bioinformatics/

Bioinformatics Services / CRO Services

RASA Life Sciences — Wed, 06 Nov 2019 00:33:11 -0600

RASA is set to provide premium technical and scientific services in a form of solutions, product development and training. .We are also very proficient in providing the high quality Research & Development services in life science informatics field like Next Generation Sequencing (NGS) Data Analysis,Computational Drug Discovery, Bioinformatics, Chemo-informatics and BIO-IT.

RASA offers faster, better and cost effective cutting edge technology solutions to chemical and life science research and industry. We provide our customers with A seamless model of wide expertise and comprehensive platforms. Our Value is to take our customers

gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output

Rahul Nayak — Fri, 24 Jan 2020 06:04:40 -0600

gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser.

gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

LoFreq*: A sequence-quality aware, ultra-sensitive variant caller for NGS data

BioStar — Tue, 18 Feb 2020 03:24:22 -0600

LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.

https://github.com/CSB5/lofreq

http://csb5.github.io/lofreq/installation/

https://github.com/CSB5/lofreq/tree/master/dist

Address of the bookmark: http://csb5.github.io/lofreq/