BOL: Related items

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

List of tools frequently used while genome assembly

BioStar — Tue, 22 Jan 2019 09:39:02 -0600

List of tools frequently used while genome assembly:

I have used the following assemblers

Spades (v. 3.10.1)
CANU (v. 1.6)
Unicycler (v. v0.4.1)
Miniasm (v. 0.2-r137-dirty)

I have used the following mappers

minimap2 (v. 2.0rc1-r232)
minimap (v. 0.2-r124-dirty)
bwa (v. 0.7.12-r1039)

I have used the following polishing tools

Racon (v. not available)
Pilon (v. 1.18)
Nanopolish (v. 0.8.3)

I have used the following tools to assess genome assembly characteristics

ANI.pl (https://github.com/chjp/ANI)
CheckM (v. 1.0.7)
Prokka (v. 1.12)
QUAST (v. 2.3)
mummer (v. not available)

If you have any ideas or superior tools we have missed please let us know in the comments.

Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.

BioStar — Thu, 09 Apr 2020 04:56:09 -0500

Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.

More at https://dahak-metagenomics.github.io/dahak/

Address of the bookmark: https://github.com/dahak-metagenomics/dahak

Frequent parameters for bioinformatics tools !

BioStar — Tue, 27 Oct 2020 19:42:32 -0500

Third party executable parameters and options.

Trimmomatic

“ILLUMINACLIP:...:2:30:10”

“LEADING:15”

“TRAILING:15”

“SLIDINGWINDOW:4:20”

“MINLEN:20”

“TOPHRED33”

Filtlong

--min_length 500

--min_mean_q 85

--min_window_q 65

FastQ Screen

--aligner bowtie2' (bwa for PacBio)

--subset 1000 (for PacBio)

SPAdes

--careful

--disable-gzip-output

--cov-cutoff auto

--phred-offset 33

HGAP

Pbalign.task_options.min_accuracy: 70

Pbalign.task_options.no_split_subreads: false

Genomic_consensus.task_options.min_confidence: 40

falcon_ns.task_options.HGAP_GenomeLength_str:

6000000

Pbcoretools.task_options.read_length: 0

Genomic_consensus.task_options.use_score: 0

Pbalign.task_options.min_length: 50

Pbalign.task_options.algorithm_options: --minMatch 12

--bestn 10 --minPctSimilarity 70.0

Pbalign.task_options.hit_policy: randombest

Pbcoretools.task_options.other_filters: rq >= 0.7

Pbalign.task_options.concordant: false

Genomic_consensus.task_options.min_coverage: 5

falcon_ns.task_options.HGAP_SeedCoverage_str: 30

falcon_ns.task_options.HGAP_AggressiveAsm_bool: false

Genomic_consensus.task_options.algorithm: best

falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1

Genomic_consensus.task_options.diploid: false

MeDuSa

-random 100

Prokka

--usegenus

--force

--addgenes

--rfam

--rawproduct

cmsearch (taxonomy, 16S)

--rfam

--noali

blastn (taxonomy, 16S)

-evalue 1E-10

blastn (MLST)

-ungapped

-dust no

-evalue 1E-20

-word_size 32

-culling_limit 2

-perc_identity 95

blastp (VF)

-culling_limit 2

RGI (ABR)

--input_type contig

bowtie2 (mapping)

--sensitive

minimap2 (mapping)

-a

-x map-ont

samtools mpileup (SNP detection)

-uRI

bcftools call (SNP detection)

--variants-only

--skip-variants indels

--output-type v

--ploidy 1

-c

SNPsift filter (SNP detection)

"( QUAL >= 30 ) & (( na FILTER ) | (FILTER = 'PASS')) &

( DP >= 20 ) & ( MQ >= 20 )"

SNPeff ann (SNP detection)

-nodownload

-no-intron

-no-downstream

-no SPLICE_SITE_REGION

-upDownStreamLen 250

bcftools consensus

(phylogenetic tree)

--haplotype 1

fasttreemp

-nt

-boot 100

roary

-e

-n

-cd 100

-g 100000

Bioinformatics tools for telomere to telomere assembly !

BioStar — Tue, 17 Aug 2021 13:17:09 -0500

● Merfin – k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)
● PanGenie – algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)
● SQANTI3 – an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Rocío Amorín de Hegedüs @rocioadh)
● tama (Transcriptome Annotation by Modular Algorithms) – software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo @GenomeRIK)
● pbaa (PacBio Amplicon Analysis) – separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg @zevkronenberg)
● bellerophon – analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng @Yuanyuan929)
● svpack – tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)
● JumboDB – tool for de Bruijn graph construction (Anton Bankevich @AntonBankevich)
● uLTRA – tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin @krsahlin)
● LeafGo – workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini @ermini_luca)

Reference:

https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/

Comparative genomics visualisation tools !

Neel — Thu, 17 Feb 2022 05:37:55 -0600

Comparative genomics visualisation tools !

Address of the bookmark: https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&selected=%23BRIG&tag=Comparative

Bioinformatic tools for pathogens informatics at CVR

Abhi — Sat, 08 Jun 2024 15:59:46 -0500

Novel sequencing and analytical approaches focused on studying viruses and virus-host interactions. Below you will find summaries and links to a number of bioinformatic tools that have been developed @ CVR.

DIGS

The database-integrated genome-screening (DIGS) tool provides a framework for implementing automated in silico screening of sequence databases using BLAST in combination with a relational database (MySQL).

DisCVR

DisCVR is a Diagnostic tool for detecting known human viruses in clinical samples from Next-Generation Sequencing (NGS) data. The tool uses a simple and straightforward Graphical User Interface and is optimized on Windows OS without compromising speed and accuracy.

DiversiTools

DiversiTools is a computational tool that is specifically tailored towards viral HTS data sets and the analysis of the underlying viral populations that they represent. It was initially developed in collaboration with a number of virologists interested in characterising the intra-host diversity of viral populations and studying their evolution across transmission chains at the micro-evolutionary scale.

GLUE

GLUE is a flexible data-centric bioinformatics environment for virus sequence data, with a focus on virus evolution and genomic variation. GLUE has been applied to a range of viruses. A GLUE-based resource focused on Hepatitis C virus is HCV-GLUE.

Tanoti

Tanoti is a BLAST guided reference based short read aligner. It is developed for maximising alignment in highly variable next generation sequence data sets (Illumina).

ViCTree

ViCTree is a bioinformatic framework that automatically selects new candidate virus sequences from GenBank, generates multiple sequence alignments, calculates a maximum likelihood phylogeny and integrates the sequences into the existing phylogenetic trees. For more information click here.

Viral Host Predictor

Viral Host Predictor provides a fast and simple way to predict the hosts and vectors of RNA viruses from viral sequences.

GRACy

GRACy is a bioinformatic tool designed for the analysis of Illumina data originated from Human cytomegalovirus samples. GRACy can be used to perform read quality filtering, genotyping, de novo assembly, variant detection, annotation and data submission to public database.

LoReTTA

LoReTTA (Long Read Template Targeted Assembler) is a reference assisted de novo assembler specifically designed to deal with PacBio reads generated from viral genomes.

BingleSeq

BingleSeq is a R-package enables the user-friendly analysis of count tables obtained by both Bulk RNA-Seq and single-cell RNA-Seq protocols. The development of BingleSeq focused on providing a flexible and intuitive user experience.

Bioinformatics -- Understanding of living systems through information science

Wed, 14 Aug 2013 11:50:17 -0500

Recently, the progress of the Human Genome Project, aiming to decode all human DNA sequences, has highlighted a research field called bioinformatics. In this new field, computers and techniques from information science are not just used as tools to advance life science research; they're expected to have a major impact on how we think about the life sciences. Q. The main feature of bioinformatics is, it utilizes computers to analyze life. One is example is the genome. In all organisms, DNA contains genetic information, and this is called the genome. But the amount of information involved is huge, so recently, it's been read using next-generation sequencers, and analyzed by computers. In bioinformatics research, what we do is utilize those genome information to investigate the principles of life. As an organism evolves, its genome sequence changes through sudden mutations. Additionally, at the genome level, mutations called rearrangements, such as inversions, transpositions, and duplications, occur. The genome comparison system developed by the Sakakibara Lab calculates homologous sequences called anchors, which are conserved between species. If the genome is considered as a long text, then anchors can be thought of as words. Q. We're coming to understand the genomes of various organisms - not just humans, but monkeys, chimpanzees, bacteria, and so on. The first method used to analyze a genome is comparing it with the genomes of other organisms, to see where it's the same and where it's different. In that way, the content of the genome is decoded bit by bit, using computers. By contrast, in our method, we've developed software called Murasaki, which we also use to analyze large genomes, by comparing them with those of other organisms. The Sakakibara Lab uses a next-generation sequencer at Keio University, along with a cluster machine with hundreds of CPUs. In this way, the Lab is analyzing genome mutations that cause cancer, and the genome of the natto production strain Bacillus subtilis. Until now, genome analysis could only be done in national-scale projects. But now, next-generation sequencer development has made genome analysis possible in an ordinary lab. In a world-first achievement, the Sakakibara Lab has decoded the natto bacillus genome, through analysis using Keio's next-generation sequencer. Q. In the future, biology and the life sciences may become almost entirely information science and computer science. And in healthcare, that may enable us, for example, to predict whether individuals are susceptible to cancer, or to certain lifestyle-related diseases, by understanding their personal genome data. So, I think it's amply possible that we can make use of such information effectively, to help people live longer and be free from disease, by thinking about their lifestyle habits. Bioinformatics is only two decades old. In this field, many areas are still unknown. Professor Sakakibara, having been involved since the beginning, will continue tackling new, challenging research projects.

ForBio and UiB course: Introduction to phylogenetic methods

Rahul Nayak — Mon, 16 Dec 2019 09:39:12 -0600

The is an introductory course that is aimed at students who will need to preform phylogenetic analyses in their work, but who have little or no experience with phylogenetic analyses. The ForBio component of the course is focused on the practical aspects of phylogenetic analyses and students that have not attended the theoretical part of the course are expected to have read the relevant literature. The course will cover all basic aspects of phylogenetic analyses with emphasis on use of DNA data. Students will learn how to prepare their data, explore its properties and how to analyze it using distance, parsimony, likelihood and Bayesian methods. In the last two days students will also get an introduction to molecular dating with focus on the use of BEAST and to comparative methods used to study the evolution of discrete and continuous traits.

https://www.forbio.uio.no/events/courses/2020/Bergen_Phylogenetics_2020.html

ForBio travel grants
We have changed our travel grants rules. ForBio offers both incoming and outgoing travel grants to fund collaborations between ForBio members based in Norway and taxonomic experts up to NOK 14,000. Grants are given for taxonomic training with relevance to the main research project of the applicant, and aim to allow the student to do taxonomic research with specific experts, work with particular collections, or learn new preparation techniques directly from experts. Participation in external courses, conferences, fieldwork or other kinds of activities which are not classified as expert-in-training visits are no longer eligible for support. There are two application deadlines: March 1st 2020.

useR!

Jitendra Narayan — Wed, 10 Jul 2013 14:41:49 -0500

The R project actively supports two conference series, organized regularly by members from the R community: useR! - providing a forum to the R user community - and DSC - a platform for developers of statistical software.

Recently useR! conference have been organized University of Castilla-La Mancha, Albacete, Spain.

http://www.edii.uclm.es/~useR-2013//