BOL: All site bookmarks

PERGA: A Paired-End Read Guided De Novo Assembler for Extending Contigs Using SVM and Look Ahead Approach

Rahul Nayak — Tue, 05 Jun 2018 09:57:11 -0500

PERGA - Paired End Reads Guided Assembler PERGA is a novel sequence reads guided de novo assembly approach which adopts greedy-like prediction strategy for assembling reads to contigs and scaffolds. Instead of using single-end reads to construct contig, PERGA uses paired-end reads and different read overlap sizes from O ≥ Omax to Omin to resolve the gaps and branches. Moreover, by constructing a decision model using machine learning approach based on branch features, PERGA can determine the correct extension in 99.7% of cases. PERGA will try to extend the contigs by all feasible nucleotides and determine if these multiple extensions due to sequencing errors or repeats by using looking ahead technology, and it also try to separate the different repeats of nearby genomic regions to make the assembly result more longer and accurate. The simulated E.coli paired-end reads data are generated using GemSim (KE McElroy, F Luciani, T Thomas. Gemsim: General, Error-Model Based Simulator of Next-Generation Sequencing Data. BMC Genomics 2012, 13:74), with coverage 50x, 60x, 100x, read lengths 100-bp, and can be downloaded from https://github.com/zhuxiao/data_PERGA.

Address of the bookmark: https://github.com/hitbio/PERGA

EAGLER: a scaffolding tool for long reads.

Jit — Mon, 04 Jun 2018 05:26:03 -0500

EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.

The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:

Mac OS X 10.11.1
Mac OS X 10.10.3
Ubuntu 14.04 LTS

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf

Address of the bookmark: https://github.com/mculinovic/EAGLER

“One code to find them all”: a perl tool to conveniently parse RepeatMasker output files

Poonam Mahapatra — Mon, 04 Jun 2018 03:45:15 -0500

One code to find them all is a set of perl scripts to extract useful information from RepeatMasker about transposable elements, retrieve their sequences and get some quantitative information. Assemble RepeatMasker hits into complete TE copies, including LTR-retrotransposon Retrieve corresponding TE sequences, and flanking sequences, from the local fasta files Compute summary statistics for each TE family (number of TE copies, genome coverage...) Ambiguous cases such as nested TE can be assembled into copies automatically or manually Allow for working with a TE user-defined library Allow for working with only a user-chosen set of TE families http://doua.prabi.fr/software/one-code-to-find-them-all

Address of the bookmark: http://doua.prabi.fr/software/one-code-to-find-them-all

MCMCTREE: a phylogenetic program for Bayesian estimation of species divergence times

Poonam Mahapatra — Sat, 02 Jun 2018 07:40:06 -0500

MCMCTREE is a phylogenetic program for Bayesian estimation of species divergence times using soft fossil constraints under various molecular clock models. This is part of the PAML package. In this tutorial I will analyze an easy example modified from dataset of Inoue et al. (2010). Here we conduct a commonly used time estimation method, "Approximate Likelihood Method", for the datasets including more than 10 species.

Address of the bookmark: http://www.fish-evol.com/mcmctreeExampleVert6/text1Eng.html

GLEAN: an unsupervised learning system to integrate disparate sources of gene structure evidence

Poonam Mahapatra — Sat, 02 Jun 2018 07:38:33 -0500

GLEAN is an unsupervised learning system to integrate disparate sources of gene structure evidence (gene model predictions, EST/protein genomic sequence alignments, SAGE/peptide tags, etc) to produce a consensus gene prediction, without prior training.

Address of the bookmark: https://sourceforge.net/projects/glean-gene/

Gblocks: eliminates poorly aligned positions and divergent regions of a DNA or protein alignment

Poonam Mahapatra — Sat, 02 Jun 2018 07:36:05 -0500

Gblocks eliminates poorly aligned positions and divergent regions of a DNA or protein alignment so that it becomes more suitable for phylogenetic analysis. This server implements the most important features of the Gblocks program to make its use as simple as possible without loosing the functionality that it is necessary in most of the cases. Other options can be changed in the stand-alone program. You can see here an example output file showing the blocks selected from a protein alignment. Further information can be found in the online documentation.

Address of the bookmark: http://molevol.cmima.csic.es/castresana/Gblocks_server.html

Ranbow: a haplotype assembler for polyploid genomes

Jit — Fri, 01 Jun 2018 07:21:54 -0500

Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function: ranbow hap: for haplotyping ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads ranbow phylo: for the phylogenetic analysis

Address of the bookmark: https://www.molgen.mpg.de/ranbow

BFC: a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data

Jit — Thu, 31 May 2018 09:35:23 -0500

BFC is a standalone high-performance tool for correcting sequencing errors from Illumina sequencing data. It is specifically designed for high-coverage whole-genome human data, though also performs well for small genomes. The BFC algorithm is a variant of the classical spectrum alignment algorithm introduced by Pevzner et al (2001). It uses an exhaustive search to find a k-mer path through a read that minimizes a heuristic objective function jointly considering penalties on correction, quality and k-mer support. This algorithm was first implemented in my fermi assembler and then refined a few times in fermi, fermi2 and now in BFC. In the k-mer counting phase, BFC uses a blocked bloom filter to filter out most singleton k-mers and keeps the rest in a hash table (Melsted and Pritchard, 2011). The use of bloom filter is how BFC is named, though other correctors such as Lighter and Bless actually rely more on bloom filter than BFC. https://github.com/lh3/bfc

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

CrossMap: a program for convenient conversion of genome coordinates

Jit — Thu, 31 May 2018 06:00:47 -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

SEX-DETector: A Probabilistic Approach to Study Sex Chromosomes in Non-Model Organisms

Surabhi Chaudhary — Wed, 30 May 2018 15:57:31 -0500

SEX-DETector is a probabilistic method that relies on RNAseq data from a cross (parents and progeny of each sex) to infer autosomal and sex-linked genes (genes located on the non recombining part of sex chromosomes).

How does SEX-DETector work?

SEX-DETector does not require prior sequencing of a reference genome: the same sequencing data can be used for the assembly and for the mapping of the reads. A full documentation on the pipeline can be found here.

we recommend Trinity for the assembly.
Trinity components should be merged with cap3. Our code to perform the merging is available here.
We recommend BWA for mapping of the reads.
When the mapping has been perfomed, the individuals need to be genotyped; SEX-DETector takes files produced by Reads2snp (which is available for download on the PopPhyl website) as input.

Address of the bookmark: http://lbbe.univ-lyon1.fr/-SEX-DETector-.html?lang=eg