BOL: Related items

OPERA : Optimal Paired-End Read Assembler

Jit — Fri, 09 Sep 2016 05:28:58 -0500

OPERA (Optimal Paired-End Read Assembler) is a sequence assembly program (http://en.wikipedia.org/wiki/Sequence_assembly). It uses information from paired-end/mate-pair/long reads to order and orient the intermediate contigs/scaffolds assembled in a genome assembly project, in a process known as Scaffolding. OPERA is based on an exact algorithm that is guaranteed to minimize the discordance of scaffolds with the information provided by the paired-end/mate-pair/long reads (for further details see Gao et al, 2011).

Note that since the original publication, we have made significant changes to OPERA (v1.0 onwards) including refinements to its basic algorithm (to reduce local errors, improve efficiency etc.) and incorporated features that are important for scaffolding large genomes (multi-library support, better repeat-handling etc.), in addition to other scalability and usability improvements (bam and gzip support, smaller memory footprint). We therefore encourage you to download and use our latest version: OPERA-LG. In our benchmarks, it has significantly improved corrected N50 and reduced the number of scaffolding errors. Furthermore, our latest release contains the wrapper script OPERA-long-read that enables scaffolding with long-reads from third-generation sequencing technologies (PacBio or Oxford Nanopore). The manuscript describing the new features and algorithms is available at Genome Biology. We look forward to getting your feedback to improve it further.

Address of the bookmark: https://sourceforge.net/p/operasf/wiki/The%20OPERA%20wiki/

Ribbon !!

Jit — Fri, 21 Oct 2016 04:54:30 -0500

Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.

Script at https://github.com/MariaNattestad/ribbon

Address of the bookmark: http://genomeribbon.com/

eFORGE.v1.2

Jit — Fri, 28 Oct 2016 09:06:59 -0500

The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.

Address of the bookmark: http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation

R Graphical Cookbook by Winston Chang

Abhimanyu Singh — Fri, 04 Nov 2016 12:50:30 -0500

R Graphical Cookbook by Winston Chang

A very nice book by Winston Chang for R ethusiast. The R code presented in these pages is the R code actually used to produce the Figures in the book. There will be differences compared to the code chunks shown in the text of the book, but in most cases the differences will be that these pages contain additional code to lay out multiple plots on a single "page".

The code presented for each figure is self-contained, i.e., all code required to produce the figure is included. This means that there is sometimes considerable overlap of code between several figures In some cases, it may be necessary to install an add-on package from CRAN to get the code to run.

More books at http://www.e-reading.club/bookreader.php/137370/C486x_APPb.pdf

SGA: String Graph Assembler

Jit — Thu, 08 Dec 2016 05:08:59 -0600

SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads.

More at

https://github.com/jts/sga

SGA dependencies:
-google sparse hash library (http://code.google.com/p/google-sparsehash/)
-the bamtools library (https://github.com/pezmaster31/bamtools)
-zlib (http://www.zlib.net/)
-(optional but suggested) the jemalloc memory allocator (http://www.canonware.com/jemalloc/download.html)

Address of the bookmark: https://github.com/jts/sga

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

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

Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome

BioStar — Wed, 22 Jul 2020 10:11:13 -0500

We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

More at https://pubmed.ncbi.nlm.nih.gov/20494974/

Address of the bookmark: http://www.sequenceontology.org/cgi-bin/soba.cgi

Jvarkit : Java utilities for Bioinformatics

Jit — Fri, 08 Jun 2018 09:31:55 -0500

Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

Address of the bookmark: http://lindenb.github.io/jvarkit/

BISR Jaipur

Tue, 07 Jul 2015 23:12:26 -0500

The Bioinformatics Centre at BISR has created an infrastructure for providing facilities to the users working in the field of Biological Sciences. The users of Rajasthan, Jaipur in particular, are using facilities available at the Bioinformatics Centre extensively. The centre has leased line Internet connection as well latest Bioinformatics software for sequence and structure analysis. The centre provides the following services:

Bioinformatics supports to researchers
Customized training in Bioinformatics for researchers and faculty members
Support in Installing, implementing and maintaining software on computer.
Create awareness for taking preventive measure against data security
Organize workshops on thrust ares of Bioinformatics
Research Training to students of Biotechnology and Bioinformatics

More at http://bioinfo.bisr.res.in/index.php