BOL: Related items

Liftoff: An accurate GFF3/GTF lift over pipeline

Neel — Sun, 20 Dec 2020 01:36:37 -0600

Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated “chain” file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.

Address of the bookmark: https://github.com/agshumate/Liftoff

LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets

LEGE — Fri, 17 Sep 2021 01:57:02 -0500

The pipeline was developed based on a popular workflow framework Nextflow, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report. LncPipe allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.

Ref https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/

Address of the bookmark: https://github.com/likelet/LncPipe

iMAGine - in silico MetAGenomics pipeline

BioStar — Sat, 06 Jul 2024 04:32:18 -0500

iMAGine is a metagenomic workflow which includes filtering, assembling, and binning.

This workflow includes the following tools which are needed to be installed in the system.

Address of the bookmark: https://github.com/avishekdutta14/iMAGine

Latest paper on comparison of mapping tools

Rahul Agarwal — Tue, 03 Sep 2013 18:00:38 -0500

A. Hatem, D. Bozdag, A. E. Toland, U. V. Catalyurek "Benchmarking short sequence mapping tools" BMC Bioinformatics, 14(1):184, 2013.

http://bmi.osu.edu/hpc/software/benchmark/

http://bmi.osu.edu/hpc/software/pmap/pmap.html

Other similiar papers:

http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022

http://bioinformatics.oxfordjournals.org/content/28/24/3169

Some new Mapping tool links:

GSNAP

http://research-pub.gene.com/gmap/

RMAP

http://rulai.cshl.edu/rmap/

mrsFAST

http://mrsfast.sourceforge.net/Home

http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/

BFAST

http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page

SHRiMP (for AB SOLiD color-space reads)

http://compbio.cs.toronto.edu/shrimp/

RazerA 3

http://www.seqan.de/projects/razers/

Address of the bookmark: http://www.biomedcentral.com/1471-2105/14/184

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

The 8000 years old Tibetian gene mutation !!!

Neel — Wed, 20 Aug 2014 21:57:44 -0500

A new study has provided insight into how gene mutation around 8,000 years ago helped Tibetans' to survive in the thin air on the Tibetan Plateau, where an average elevation is of 14,800 feet.

A study led by University of Utah scientists is the first to find a genetic cause for the adaptation, a single DNA base pair change that dates back 8,000 years and demonstrate how it contributes to the Tibetans' ability to live in low oxygen conditions.

About 8,000 years ago, the gene EGLN1 changed by a single DNA base pair. Today, a relatively short time later on the scale of human history, 88 percent of Tibetans have the genetic variation, and it was virtually absent from closely related lowland Asians. The findings indicate the genetic variation endows its carriers with an advantage.

In those without the adaptation, low oxygen caused their blood to become thick with oxygen-carrying red blood cells, an attempt to feed starved tissues, which could cause long-term complications such as heart failure. The researchers found that the newly identified genetic variation protected Tibetans by decreasing the over-response to low oxygen.

Reference: http://www.nature.com/nature/journal/v512/n7513/abs/nature13408.html

DAVI: Deep learning-based tool for alignment and single nucleotide variant identification

Jit — Tue, 16 Mar 2021 05:41:33 -0500

DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species

https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf

Address of the bookmark: https://github.com/gguptaiitd/NEAT

Calling variants in non-diploid systems

Neel — Sat, 26 Jun 2021 15:37:49 -0500

The main challenge associated with non-diploid variant calling is the difficulty in distinguishing between the sequencing noise (abundant in all NGS platforms) and true low frequency variants. Some of the early attempts to do this well have been accomplished on human mitochondrial DNA although the same approaches will work equally good on viral and bacterial genomes (Rebolledo-Jaramillo et al. 2014, Li et al. 2015).

Address of the bookmark: https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/non-dip/tutorial.html

simNGS and simLibrary – Software for Simulating Next-Gen Sequencing Data

Jit — Tue, 28 Nov 2017 06:49:11 -0600

simNGS is software for simulating observations from Illumina sequencing machines using the statistical models behind the AYB base-calling software. By default, observations only incorporate noise due to sequencing and do not incorporate effects from more esoteric sources of noise that may be present in real data ("dust", bubbles, merged clusters, sequence-heterogeneous clusters, etc). Many of these additional sources may optionally applied.

simNGS takes fasta format sequences and a file describing the covariance of noise between bases and cycles observed in an actual run of the machine, randomly generates noisy intensities representing the signals for the sequence at each cycle and calculates likelihoods for all possible base calls.

Address of the bookmark: https://www.ebi.ac.uk/goldman-srv/simNGS/

EvidentialGene: tr2aacds, mRNA Transcript Assembly Software

Rahul Nayak — Mon, 01 Oct 2018 13:13:24 -0500

Quality assessment of this mRNA Transcript Assembly Software is described in EvidentialGene_quality.

Too many transcript assemblies is much better than too few. It allows one then to apply biological criteria to pick out the best ones. Don't be misled by the "right number" of transcripts that one or other transcript assembler may produce. It is the "right sequence" you want, and now the only way to get it is to produce way too many assemblies on a good RNA data set, with several methods and several parameter settings.

Address of the bookmark: https://sourceforge.net/p/evidentialgene/blog/