BOL: Related items

AIRVF: a filtering toolbox for precise variant calling in Ion Torrent sequencing

BioStar — Fri, 22 Dec 2017 00:31:06 -0600

AIRVF that works on flowgram, raw and mapped reads and called variants to reduce artifact-driven false variant calls. Tests on sequencing data of standard reference material showed up to ∼98% reduction of false variants when combined to conventional public pipelines and ∼48% to the in-house commercial solution, with a minimal loss of sensitivity

The program with a detailed manual is available at https://sourceforge.net/projects/airvf/

Address of the bookmark: https://sourceforge.net/projects/airvf/

VG: variation graph data structures, interchange formats, alignment, genotyping, and variant calling methods

Jit — Tue, 28 Jan 2020 03:53:24 -0600

Variation graphs provide a succinct encoding of the sequences of many genomes. A variation graph (in particular as implemented in vg) is composed of:

nodes, which are labeled by sequences and ids
edges, which connect two nodes via either of their respective ends
paths, describe genomes, sequence alignments, and annotations (such as gene models and transcripts) as walks through nodes connected by edges

Address of the bookmark: https://github.com/vgteam/vg

Variant Calling Resequencing-Based Genome Inference

Abhi — Wed, 31 Jul 2024 02:02:24 -0500

Variant Calling - Resequencing-Based Genome Inference

Erik Garrison
University of Tennessee Health Science Center
Workshop on Genomics - Český Krumlov
January 12, 2024

https://evomics.org/wp-content/uploads/2024/01/Variant-calling-Workshop-on-Genomics-2024-Cesky-Krumlov.pdf

Address of the bookmark: https://evomics.org/wp-content/uploads/2024/01/Variant-calling-Workshop-on-Genomics-2024-Cesky-Krumlov.pdf

Ensembl Variation - Calculated variant consequences

Jit — Sun, 09 Sep 2018 19:17:37 -0500

For each variant that is mapped to the reference genome, we identify all overlapping Ensembl transcripts. We then use a rule-based approach to predict the effects that each allele of the variant may have on each transcript. The set of consequence terms, defined by the Sequence Ontology (SO), that can be currently assigned to each combination of an allele and a transcript is shown in the table below. Note that each allele of each variant may have a different effect in different transcripts.

Address of the bookmark: https://www.ensembl.org/info/genome/variation/prediction/predicted_data.html

Snippy: Rapid haploid variant calling and core SNP phylogeny

Neel — Sat, 11 Aug 2018 11:06:56 -0500

Snippy finds SNPs between a haploid reference genome and your NGS sequence reads. It will find both substitutions (snps) and insertions/deletions (indels). It will use as many CPUs as you can give it on a single computer (tested to 64 cores). It is designed with speed in mind, and produces a consistent set of output files in a single folder. It can then take a set of Snippy results using the same reference and generate a core SNP alignment (and ultimately a phylogenomic tree).

snippy --cpus 16 --outdir mysnps --ref Listeria.gbk --R1 FDA_R1.fastq.gz --R2 FDA_R2.fastq.gz

Address of the bookmark: https://github.com/tseemann/snippy

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

BioStar — Mon, 05 Aug 2024 23:01:29 -0500

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

Using state of the art tools, easily extended for other viruses
Tool and database updates for critical components via Conda
Built using modern design patterns with Conda and Snakemake
Extensible and easy to customize
Submission Ready Genomes
Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

Address of the bookmark: https://ikim-essen.github.io/uncovar/

CRBHits: From Conditional Reciprocal Best Hits to Codon Alignments and Ka/Ks in R

Shruti Paniwala — Wed, 11 Nov 2020 23:06:03 -0600

CRBHits is a coding sequence (CDS) analysis pipeline in R (R Core Team, 2019). It reimplements the Conditional Reciprocal Best Hit (CRBH) algorithm crb-blast and covers all necessary steps from sequence similarity searches, codon alignments to Ka/Ks calculations and synteny. The new R package targets ecology, population and evolutionary biologists working in the field of comparative genomics.

Address of the bookmark: https://gitlab.gwdg.de/mpievolbio-it/crbhits

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/

You and your friend have similar DNA !!!

Jit — Sun, 27 Jul 2014 20:44:05 -0500

New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.

Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes — a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.

The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.

Reference:

http://www.pnas.org/content/111/Supplement_3/10796.full

Image : http://i.kinja-img.com

QuasiModo - Quasispecies Metric Determination on Omics

Neel — Sat, 26 Jun 2021 15:22:56 -0500

This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.

https://academic.oup.com/bib/article/22/3/bbaa123/5868070

Address of the bookmark: https://github.com/hzi-bifo/Quasimodo