BOL: Related items

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data

Jit — Mon, 06 Aug 2018 17:24:53 -0500

NextSV, a meta SV caller and a computational pipeline to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purpose. The output of NextSV is in ANNOVAR-compatible bed format. Users can easily perform downstream annotation using ANNOVAR and disease gene discovery using Phenolyzer.

Address of the bookmark: https://github.com/Nextomics/NextSV

BamView: a free interactive display of read alignments in BAM data files

Neel — Fri, 09 Nov 2018 13:43:22 -0600

To run the application on UNIX from the downloaded jar file run the UNIX:

java -mx512m -jar BamView.jar

and extra command line options are given when '-h' is used:

java -jar BamView.jar -h

BAM files can be specified on the command line with the '-a' option:

java -mx512m -jar BamView.jar -a pathToFile/sorted.bam

If a BAM filename is not given on the command line BamView will prompt for a file to be entered. The BAM index file should have the same name as the BAM file but with a '.bai' suffix. Multiple BAM files can be loaded and overlaid in the viewer. To make this easier BamView will read in files that contain a list of filenames.

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

ZENBU: a collaborative, omics data integration and interactive visualization system

BioJoker — Fri, 04 Jan 2019 13:35:26 -0600

ZENBU is a data integration, data analysis, and visualization system enhanced for RNAseq, ChipSeq, CAGE and other types of next-generation-sequence-tag (NGS) based data. ZENBU allows for novel data exploration through "on-demand" data processing and interactive linked-visualizations and is able to make many-views from the same primary sequence alignment data which users can uploaded from BAM, BED, GFF and tab-text files.
Please check our documentation wiki for details on how to use the system, or check out some of the views above.

Address of the bookmark: http://fantom.gsc.riken.jp/zenbu/

OMTools: a software package for visualizing and processing optical mapping data

BioJoker — Fri, 29 Mar 2019 01:21:54 -0500

OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses.

https://github.com/TF-Chan-Lab/OMTools

Address of the bookmark: https://github.com/TF-Chan-Lab/OMTools

DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Jit — Sat, 25 Jan 2020 13:28:09 -0600

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant

pbmm2:A minimap2 frontend for PacBio native data formats

BioStar — Tue, 18 Feb 2020 03:36:22 -0600

pbmm2 is a SMRT C++ wrapper for minimap2's C API. Its purpose is to support native PacBio in- and output, provide sets of recommended parameters, generate sorted output on-the-fly, and postprocess alignments. Sorted output can be used directly for polishing using GenomicConsensus, if BAM has been used as input to pbmm2. Benchmarks show that pbmm2 outperforms BLASR in sequence identity, number of mapped bases, and especially runtime. pbmm2 is the official replacement for BLASR.

Address of the bookmark: https://github.com/PacificBiosciences/pbmm2

Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Jit — Thu, 28 May 2020 21:57:03 -0500

Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data

BioStar — Thu, 26 Nov 2020 11:05:04 -0600

The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an a priori binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings:

1) A cell line expressing or lacking single TF,

2) Breast tumors divided along PAM50 designations

3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype

4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels.

In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.

More at https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg

Address of the bookmark: https://github.com/asroopra/MAGIC

Refseq viraal genome sequences !

Jit — Sat, 11 Dec 2021 08:35:18 -0600

List of all viruses on NCBI

https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/

Address of the bookmark: https://ftp.ncbi.nlm.nih.gov/refseq/release/viral/