BOL: Related items

R Graphs !!

Jit — Fri, 04 Nov 2016 10:48:00 -0500

The blog is a collection of script examples with example data and output plots. R produce excellent quality graphs for data analysis, science and business presentation, publications and other purposes. Self-help codes and examples are provided. Enjoy nice graphs !!

Address of the bookmark: http://rgraphgallery.blogspot.be/

Comparative genomics educational material and papers bookmarks

Jit — Wed, 09 Nov 2016 16:23:30 -0600

Alignment of the porcine genome against seven other mammalian genomes (Supplementary Information) identified homologous synteny blocks (HSBs). Using porcine HSBs and stringent filtering criteria, 192 pig-specific evolutionary breakpoint regions (EBRs) were located. The number of porcine EBRs is comparable to the number of bovine-lineage-specific EBRs (100) reported earlier using a slightly lower resolution (500 kilobases (kb)), indicating that both lineages evolved with an average rate of ~2.1 large-scale rearrangements per million years after the divergence from a common cetartiodactyl ancestor ~60 Myr ago². This rate compares to ~1.9 rearrangements per million years within the primate lineage (Supplementary Table 11). A total of 20 and 18 cetartiodactyl EBRs (shared by pigs and cattle) were detected using the pig and human genomes as a reference, respectively.

Address of the bookmark: http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html

Professor (all levels) in Bioinformatics and Computational Biology

Tue, 22 Nov 2016 05:43:38 -0600

King Abdullah University of Science and Technology (KAUST) (kaust.edu.sa) is seeking a highly motivated and skilled faculty member for the Bioinformatics track whose research focuses on development of methods and tools for Bioinformatics and Computational Biology.
KAUST is an international, graduate-level research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located on the shores of the Red Sea in Saudi Arabia, KAUST offers superb research facilities, generous assured research funding, and internationally competitive salaries, attracting top international faculty, scientists, engineers, and students to conduct fundamental and goal-oriented research to address the world’s pressing scientific and technological challenges in the areas of food, water, energy, and the environment.
The successful applicant is expected to develop world-leading research in domain of bioinformatics/computational biology with focus on development of novel computational approaches for efficient and accurate methods of analyzing biological phenomena at molecular level. The faculty member will be part of the Computational Bioscience Research Center (CBRC) within the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division. The position will remain open until filled.

Requirements:

PhD or equivalent in a Computer Science, Mathematics or Engineering discipline. Candidates should be well-established within the research field relevant to the position grade. They should demonstrate original research and experience at the highest international level.

Responsibilities and tasks:

Research competence in the following areas is preferred:
Analysis of next generation sequencing (NGS) and other ‘omics’ data (e.g. CAGE, ChIP-Seq, DHS, RNA-Seq, Ribo-Seq, proteomic, metabolic and NMR spectra, etc.).
Signaling, regulatory and metabolic pathways analysis.
Development of tools (web-based and standalone) suited for efficient computational biology/bioinformatics.

Visit cemse.kaust.edu.sa to apply.

EXCAVATOR2tool

Bulbul — Wed, 30 Nov 2016 04:09:19 -0600

EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.
EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it’s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.

Address of the bookmark: https://sourceforge.net/projects/excavator2tool/

MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation

Neel — Thu, 15 Dec 2016 05:47:35 -0600

MyPro is an improved genomics software pipeline for prokaryotic genomes. MyPro is user-friendly and requires minimal programming skills. High-quality prokaryotic genome assembly and annotation can be obtained with ease. It performed better than de novo assemblers and contig integration software. Produces more contiguous assemblies, higher N50 values and lower number of contigs.

More at https://sourceforge.net/projects/sb2nhri/files/MyPro/

Address of the bookmark: http://www.sciencedirect.com/science/article/pii/S0167701215001207

GMOL: An Interactive Tool for 3D Genome Structure Visualization

Jit — Wed, 21 Mar 2018 12:25:20 -0500

GMOL was developed based upon our multi-scale approach that allows a user to scale between six separate levels within the genome. With GMOL, a user can choose any unit at any scale and scale it up or down to visualize its structure and retrieve corresponding genome sequences.

Address of the bookmark: https://www.nature.com/articles/srep20802

GAM-NGS: genomic assemblies merger for next generation sequencing

Jit — Mon, 19 Dec 2016 06:07:05 -0600

GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weightedgraph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.

Address of the bookmark: https://github.com/vice87/gam-ngs

Genome Assembly Tutorial

Abhimanyu Singh — Tue, 20 Dec 2016 07:56:01 -0600

If genomes were completely random sequences in a statistical sense, 'overlap-consensus-layout' method would have been enough to assemble large genomes from Sanger reads. In contrast, real genomes often have long repetitive regions, and they are hard to assemble using overlap-consensus-layout approach. De Bruijn graph-based assembly approach was originally proposed to handle the assembly of repetitive regions better.

More at http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

Address of the bookmark: http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

Mauve: a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion

Jit — Sat, 24 Dec 2016 09:20:53 -0600

Mauve is a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion. Multiple genome alignments provide a basis for research into comparative genomics and the study of genome-wide evolutionary dynamics.

Mauve has been developed with the idea that a multiple genome aligner should require only modest computational resources. It employs algorithmic techniques that scale well in the lengths of sequences being aligned. For example, a pair of Y. pestis genomes can be aligned in under a minute, while a group of 9 divergent Enterobacterial genomes can be aligned in a few hours. However, the current algorithm’s compute time (progressiveMauve) scales cubically in the number of genomes to align, making it unsuitable for datasets containing more than 50-100 bacterial genomes.

Address of the bookmark: http://darlinglab.org/mauve/mauve.html

FSA: Fast Statistical Alignment

Jit — Mon, 06 Feb 2017 04:26:01 -0600

FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in "Posterior Decoding Methods for Optimization and Control of Multiple Alignments."

FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:

FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.
FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.
FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.
The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and movie at the top of the page).

You can see more information on the FAQ.

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