BOL: Related items

SWALO

Jit — Wed, 30 Nov 2016 05:06:05 -0600

SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.

Download

Git repository of SWALO is at https://github.com/atifrahman/SWALO.

Address of the bookmark: https://atifrahman.github.io/SWALO/

Cutadapt

Bulbul — Wed, 14 Dec 2016 09:59:52 -0600

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.

If you use cutadapt, please cite DOI:10.14806/ej.17.1.200 .

More at https://github.com/marcelm/cutadapt

Address of the bookmark: http://cutadapt.readthedocs.io/en/stable/guide.html

PRISM

Jit — Sat, 10 Dec 2016 15:19:40 -0600

PRISM is a software for split read (reads which span across a structrual variant -- SV ) mapping and SV calling from the mapping result. PRISM is able to detect small insertions and abitrary size deletions, inversions and tandom duplications with the direction of discordant read pairs. PRISM_CTX is a tool for detecting inter-chromosome trans-location events.

PRISM and PRISM_CTX were originally designed and written by Michael Brudno and Yue Jiang, The original PRISM publication can be found here.

The authors may be contacted via e-mail at: prism at cs.toronto.edu.

Additional information is available in the PRISM README file and PRISM_CTX README file.

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

Address of the bookmark: http://compbio.cs.toronto.edu/prism/

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

MeGAMerge: A tool to merge assembled contigs, long reads from metagenomic sequencing runs

Jit — Mon, 19 Dec 2016 09:42:15 -0600

MeGAMerge

MeGAMerge (A tool to merge assembled contigs, long reads from metagenomic sequencing runs)

Description

MeGAMerge is a perl based wrapper/tool that can accept any number of sequence (FASTA) files containing assembled contigs of any length in Multi-FASTA format to produce an improved contig set based on OLC based assembly. All overlap parameters (Minimum Overlap Length, Identity, etc) are user-declarable at runtime. It is written to run on Linux.

Requirements:

You will need to have the following tools installed and in $PATH, or added to $binpath in the tool:

Newbler (specifically runAssembly)
Minimus2 (part of AMOS, also requires MUMmer)

Address of the bookmark: https://github.com/LANL-Bioinformatics/MeGAMerge

GKNO

Jit — Tue, 17 Jan 2017 03:35:34 -0600

gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.

More at http://gkno.me/

Address of the bookmark: http://gkno.me/

SpeedSeq

Jit — Fri, 20 Jan 2017 06:05:43 -0600

A flexible framework for rapid genome analysis and interpretation

C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.

http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3505.html

Address of the bookmark: https://github.com/hall-lab/speedseq

HiCdat

Jit — Fri, 12 Feb 2016 05:23:44 -0600

HiCdat: a fast and easy-to-use Hi-C data analysis tool

HiCdat is easy-to-use and provides solutions starting from aligned reads up to in-depth analyses. Importantly, HiCdat is focussed on the analysis of larger structural features of chromosomes, their correlation to genomic and epigenomic features, and on comparative studies. It uses simple input and output formats and can therefore easily be integrated into existing workflows or combined with alternative tools.

More at http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0678-x

Address of the bookmark: https://github.com/MWSchmid/HiCdat

Prokka: tool for the rapid annotation of prokaryotic genomes

Jit — Mon, 06 Mar 2017 03:49:57 -0600

Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.

Address of the bookmark: http://www.vicbioinformatics.com/software.prokka.shtml

sockeye

Jit — Fri, 17 Feb 2017 08:51:16 -0600

This sockeye software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3