BOL: Related items

A5-miseq

Jit — Thu, 18 Aug 2016 04:05:23 -0500

_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_.

Point to note:

There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.

Address of the bookmark: https://sourceforge.net/projects/ngopt/

CrossMap

Abhimanyu Singh — Mon, 05 Sep 2016 04:07:38 -0500

CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) <> hg19 (GRCh37), Mouse mm9 (MGSCv37) <> mm10 (GRCm38)).
It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.
CrossMap is designed to liftover genome coordinates between assemblies. It’s not a program for aligning sequences to reference genome.
We do not recommend using CrossMap to convert genome coordinates between species.

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

TEannot

Jit — Thu, 18 Aug 2016 10:02:03 -0500

We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".

Address of the bookmark: https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto

TGNet

Shruti Paniwala — Wed, 24 Aug 2016 05:36:36 -0500

Recent technological progress has greatly facilitated de novo genome sequencing. However, de novo assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis.

Visualization and quality assessment of de novo genome assemblies

Citation

This software is fully described in the paper:
Riba-Grognuz, Keller, Falquet, Xenarios & Wurm (2011) Visualization and quality assessment of de novo genome assemblies.

In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.

Software requirements

BLAT (tested with Standalone BLAT v. 32×1). Source Binaries .
Cytoscape (tested with versions 2.7.0, 2.8.2)
a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)

Address of the bookmark: https://github.com/ksanao/TGNet

Useful Bioinformatics Tools

Poonam Mahapatra — Mon, 29 Aug 2016 04:08:12 -0500

Collections of few handy tools for bioinformatician

http://molbiol-tools.ca/Convert.htm

Address of the bookmark: http://molbiol-tools.ca/Convert.htm

BRAKER: pipeline for fully automated prediction of protein coding genes with GeneMark-ES/ET and AUGUSTUS in novel eukaryotic genomes

Jit — Thu, 01 Sep 2016 08:02:59 -0500

Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.

http://www.ncbi.nlm.nih.gov/pubmed/26559507

Address of the bookmark: http://bioinf.uni-greifswald.de/bioinf/braker/

Assembly tutorial PPT

Jit — Wed, 07 Sep 2016 03:12:53 -0500

Saved Cornell University assembly workshop PPT.

Reference:

http://cbsu.tc.cornell.edu/lab/doc/assembly_workshop_20150420_lecture1.pdf

FERMI

Jit — Fri, 09 Sep 2016 05:37:13 -0500

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of
unitigs to represent all the information in raw reads.

Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index (FMD-index) as the key data structure. It is inspired by the string graph assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.

As a typical de novo assembler, fermi tends to produce contigs with slightly longer N50. However, the major weakness of fermi is the high misassembly rate. Although fermi provides a tool to fix misassemblies by using paired-end reads to achieve an accuracy comparable to other assemblers, this is not a favorable solution.

Fermi is designed to be used on a multi-core Linux machine with large shared memory. The easiest way to run fermi is to use the run-fermi.pl script. It generates a Makefile. The actual assembly is done by invoking make. Premature assembly processes can be resumed. Here is an example:

run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz > NA12878.mak
make -f NA12878.mak -j16

Address of the bookmark: https://github.com/lh3/fermi

Strudel

Anjana — Fri, 30 Sep 2016 09:47:02 -0500

Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time – there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.

Address of the bookmark: https://ics.hutton.ac.uk/strudel/

MIRO : miRNA omics

Jit — Tue, 04 Oct 2016 14:50:48 -0500

The MIRO (the miRNA omics) pipeline is a flexible and powerful tool for the analysis of miRNA (or more generall short RNA) expression using short-read deep sequencing data. In its present implementation MIRO is especially adapted for the analysis of reads generated with the Illumina sequencing platform. MIRO allows to preprocess the Solexa-reads, map them flexibly to several reference genomes using one of four different mappers, create differential gene (miRNA) expression profiles and cluster reads using one of several algorithm. MIRO output is furthermore compatible with software such as genome browsers and miRDeep.

Address of the bookmark: http://seq.crg.es/download/software/Miro/