BOL: Related items

ScaffMatch

Jit — Tue, 13 Dec 2016 10:23:56 -0600

caffMatch is a novel scaffolding tool based on Maximum-Weight Matching able to produce high-quality scaffolds from NGS data (reads and contigs). The tool is written in Python 2.7. It also includes a bash script wrapper that calls aligner in case one needs to first map reads to contigs (instead of providing .sam files).

The arguments accepted by ScaffMatch are:

-w) Working directory -- this is the directory where ScaffMatch files are stored. These are .sam files produced after mapping reads to contigs and the resulting scaffolds file `scaffolds.fa` fasta file;

-c) Contig fasta file;

-m) Command line argument with no options. It is used when .sam files are used instead of reads .fastq files. Do not use this option if you provide reads files;

-1) (Comma separated list of) either .fastq or .sam file(s) corresponding to the first read of the read pair;

-2) (Comma separated list of) either .fastq or .sam file(s) corresponding to the second read of the read pair;

-i) (Comma separated list of) insert size(s) of the library(-ies);

-s) (Comma separated list of) library(-ies) standard deviation(s) of insert size(s);

-t) Bundle threshold. Pairs of contigs supported by number of read pairs less than the value of this argument are discarded. Optional argument, by default it is equal to 5;

-g) Matching heuristics: use `max_weight` for Maximum Weight Matching heuristics with the Insertion step, use `backbone` for Maximum Weight Matching heuristics without the Insertion step, use `greedy` for Greedy Matching heuristics;

-l) Log file - where to store the logs. Optional argument. By default, stdout is used.

Address of the bookmark: http://alan.cs.gsu.edu/NGS/?q=content/scaffmatch

GARM:Genome Assembly, Reconciliation and Merging

Jit — Mon, 19 Dec 2016 06:03:02 -0600

The pipeline is based mainly implemented using Perl scripts and modules and third-party open source software like the AMOS (Myers et al., 2000) and MUMmer (Kurtz et al., 2004) packages. The pipeline was tested on Debian, Ubuntu, Fedora and BioLinux distributions. The method merges contigs or scaffolds from different assemblers using the same or different sequencing technologies. When scaffolds are provided, a process of finding probable compressions or extensions (CE) problems in the assemblies can be per-formed; contigs are joined back into scaffolds after gap recalculation

Address of the bookmark: http://garm-meta-assem.sourceforge.net/

quickmerge: A simple and fast metassembler and assembly gap filler designed for long molecule based assemblies.

Jit — Mon, 19 Dec 2016 10:23:36 -0600

quickmerge uses a simple concept to improve contiguity of genome assemblies based on long molecule sequences, often with dramatic outcomes. The program uses information from assemblies made with illumina short reads and PacBio long reads to improve contiguities of an assembly generated with PacBio long reads alone. This is counterintuitive because illumina short reads are not typically considered to cover genomic regions which PacBio long reads cannot. Although we have not evaluated this program for assemblies generated with Oxford nanopore sequences, the program should work with ONP-assemblies too.

Address of the bookmark: https://github.com/mahulchak/quickmerge

Krona

Jit — Wed, 22 Mar 2017 04:47:35 -0500

Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an Excel template or KronaTools, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see Browser support).

Address of the bookmark: https://github.com/marbl/Krona/wiki

Harvest

Jit — Tue, 31 Jan 2017 10:57:56 -0600

Harvest is a suite of core-genome alignment and visualization tools for quickly analyzing thousands of intraspecific microbial genomes, including variant calls, recombination detection, and phylogenetic trees.

Tools

Parsnp - Core-genome alignment and analysis
Gingr - Interactive visualization of alignments, trees and variants
HarvestTools - Archiving and postprocessing

Citation

Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15 (11), 1-15 [PDF]

Address of the bookmark: http://harvest.readthedocs.io/en/latest/index.html

Salzberg lab

Mon, 15 May 2017 05:14:01 -0500

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with biomedical scientists to apply these methods to current problems arising in a broad spectrum of biological and medical research areas. We’re also part of the Center for Computational Biology, a group of 20+ faculty members and their labs at Johns Hopkins working on computational, statistical, and mathematical methods that can turn massive genomic data sets into biologically and clinically useful information.

https://salzberg-lab.org/

A 3D Map of the Human Genome

Fri, 12 Dec 2014 22:27:55 -0600

Suhas Rao and Miriam Huntley (of the Aiden Lab) describe a 3D map of the human genome at kilobase resolution, revealing the principles of chromatin looping. Guest Origami Folding: Sarah Nyquist. Suhas S.P. Rao*, Miriam H. Huntley*, Neva C. Durand, Elena K. Stamenova, Ivan D. Bochkov, James T. Robinson, Adrian L. Sanborn, Ido Machol, Arina D. Omer, Eric S. Lander, Erez Lieberman Aiden. (2014). A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping. Cell.

Picard

Neel — Fri, 29 Apr 2016 08:21:54 -0500

Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the Hts-specs repository. See especially the SAM specification and the VCF specification.

Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on GitHub.

The Picard toolkit is open-source under the MIT license and free for all uses.

Enjoy!

Address of the bookmark: http://broadinstitute.github.io/picard/

CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.

Jit — Tue, 26 Apr 2016 11:38:10 -0500

Canu is a fork of the Celera Assembler designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.

Canu is a hierachical assembly pipeline which runs in four steps:

Detect overlaps in high-noise sequences using MHAP
Generate corrected sequence consensus
Trim corrected sequences
Assemble trimmed corrected sequences

Read the documentation

New release https://github.com/marbl/canu/releases

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

GAEMR

Jit — Tue, 14 Jun 2016 06:18:37 -0500

The Genome Assembly Evaluation Metrics and Reporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR’s analysis pipeline, hence enabling the generation of standard reports.

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly.

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/