BOL: Related items

pyGenomeTracks: Standalone program and library to plot beautiful genome browser tracks

Neel — Fri, 09 Nov 2018 12:34:23 -0600

pyGenomeTracks aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot:

bigwig
bed (many options)
bedgraph
links (represented as arcs)
Hi-C matrices (if HiCExplorer is installed)

Address of the bookmark: https://github.com/deeptools/pyGenomeTracks

Merqury: reference-free quality and phasing assessment for genome assemblies

Jit — Sat, 06 Jun 2020 05:38:34 -0500

Often, genome assembly projects have illumina whole genome sequencing reads available for the assembled individual. The k-mer spectrum of this read set can be used for independently evaluating assembly quality without the need of a high quality reference. Merqury provides a set of tools for this purpose.

https://github.com/marbl/meryl

Address of the bookmark: https://github.com/marbl/merqury

ARCS: scaffolding genome drafts with linked reads

Jit — Mon, 17 Dec 2018 17:40:28 -0600

ARCS requires two input files:

Draft assembly fasta file
Interleaved linked reads file (Barcode sequence expected in the BX tag of the read header or in the form "@readname_barcode" ; Run Long Ranger basic on raw chromium reads to produce this interleaved file)

Address of the bookmark: https://github.com/bcgsc/ARCS/

LTR_Finder: an efficient program for finding full-length LTR retrotranspsons in genome sequences.

Neel — Sun, 13 Jan 2019 07:05:53 -0600

LTR_Finder is an efficient program for finding full-length LTR retrotranspsons in genome sequences.

The Program first constructs all exact match pairs by a suffix-array based algorithm and extends them to long highly similar pairs. Then Smith-Waterman algorithm is used to adjust the ends of LTR pair candidates to get alignment boundaries. These boundaries are subject to re-adjustment using supporting information of TG..CA box and TSRs and reliable LTRs are selected. Next, LTR_FINDER tries to identify PBS, PPT and RT inside LTR pairs by build-in aligning and counting modules. RT identification includes a dynamic programming to process frame shift. For other protein domains, LTR_FINDER calls ps_scan (from PROSITE, http://www.expasy.org/prosite/) to locate cores of important enzymes if they occur.

Address of the bookmark: https://github.com/xzhub/LTR_Finder

CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants

BioJoker — Tue, 09 Apr 2019 07:23:37 -0500

Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.

https://www.nature.com/articles/nm.3975

Address of the bookmark: https://www.nature.com/articles/nm.3975

ALF--a simulation framework for genome evolution.

Jit — Tue, 22 Oct 2019 22:05:58 -0500

Artificial Life Framework (ALF) simulates a root genome into a number of related genomes. Result files include the resulting gene sequences, true tree and true MSAs. A description of ALF can be found in the following article:

Daniel A Dalquen, Maria Anisimova, Gaston H Gonnet, Christophe Dessimoz: ALF - A Simulation Framework for Genome Evolution. Mol Biol Evol, 29(4):1115-1123, April 2012.
http://mbe.oxfordjournals.org/content/29/4/1115

Address of the bookmark: http://alfsim.org/#index

Shasta long read assembler

Jit — Tue, 14 Jan 2020 06:47:07 -0600

The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells.

Computational methods used by the Shasta assembler include:

Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.
Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10).

More at https://chanzuckerberg.github.io/shasta/index.html

Address of the bookmark: https://github.com/chanzuckerberg/shasta

Liu Lab

Tue, 04 Feb 2020 06:27:02 -0600

Shirley is a computational biologist with expertise in cancer epigenetics. Her research focuses on algorithm development and integrative mining from big data generated on microarrays, massively parallel sequencing, and other high throughput techniques to model the specificity and function of transcription factors, chromatin regulators and lncRNAs in tumor development, progression, drug response and resistance.

https://liulab-dfci.github.io/software/

shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams

Jit — Sat, 29 Feb 2020 00:39:50 -0600

shinyChromosome is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R Shiny package.

To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the Single-genome plot menu.

To cretae two-genome plot for comparison of data across two genomes, go to the Two-genome plot menu.

For the detail format of input data, check the Input data format submenu of the Help menu.

shinyChromosome is deployed at http://150.109.59.144:3838/shinyChromosome/, http://shinyChromosome.ncpgr.cn, and https://yimingyu.shinyapps.io/shinyChromosome for online use. The source code and manual of shinyChromosome are freely available at https://github.com/venyao/shinyChromosome.

https://yimingyu.shinyapps.io/shinychromosome/

https://www.sciencedirect.com/science/article/pii/S1672022919301883

Address of the bookmark: https://yimingyu.shinyapps.io/shinychromosome/

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Rahul Nayak — Fri, 01 May 2020 03:00:40 -0500

RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.

Address of the bookmark: https://github.com/AppliedBioinformatics/RefKA