BOL: Related items

QuIN’s web server

Jit — Mon, 27 Jun 2016 10:44:16 -0500

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.

AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub:https://github.com/UcarLab/QuIN/.

Address of the bookmark: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004809

Bioinformatics tools and software

Jit — Tue, 05 Jul 2016 10:02:26 -0500

USEARCH >
Extreme high-throughput sequence analysis. Orders of magnitude faster than BLAST. MUSCLE >
Multiple sequence alignment. Faster and more accurate than CLUSTALW.

UPARSE >
OTU clustering for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures. UCHIME >
Chimeric sequence detection. PILER >
De novo genome repeat finder. PILER-CR >
Detection of CRISPR repeats in bacterial genomes. QSCORE >
Compare two multiple alignments for benchmarking. PALS >
Whole-genome alignment. PREFAB >
Protein Reference Alignment Database. MSA benchmark collection >
Selected multiple alignment benchmarks in a standardized FASTA format.

Address of the bookmark: http://drive5.com/software.html

vcfR

Archana Malhotra — Fri, 19 Aug 2016 07:38:24 -0500

Most variant calling pipelines result in files containing large quantities of variant information. The variant call format (vcf) is an increasingly popular format for this data. The format of these files and their content is discussed in the vignette ‘vcf data.’ These files are typically intended to be post-processed (i.e., filtered) as an attempt to remove false positives or otherwise problematic sites. The R package vcfR provides tools to facilitate this filtering as well as to visualize the effects of choices made during this process.

Address of the bookmark: https://cran.r-project.org/web/packages/vcfR/vignettes/visualization_1.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/

pyScaf

Bulbul — Mon, 19 Dec 2016 14:20:33 -0600

pyScaf orders contigs from genome assemblies utilising several types of information:

paired-end (PE) and/or mate-pair libraries (NGS-based mode)
long reads (NGS-based mode)
synteny to the genome of some related species (reference-based mode)

Scaffolding

In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.

Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:

matches not satisfying cut-offs (--identity and --overlap)
suboptimal matches (only best match of each query to reference is kept)
and removing overlapping matches on reference.

In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on C. parapsilosis (13 Mb; CANPA) and A. thaliana (119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (Figures in dropbox, CANPA table, ARATH table).
Runs took ~0.5 min for CANPA on 4 CPUs and ~2 min for ARATH on 16 CPUs.

Important remarks:

Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.
pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no de novo assembler / scaffolder is perfect...), which breaks synteny.
pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.
pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations. Note however, this is experimental implementation!
Consider closing gaps after scaffolding.

Address of the bookmark: https://github.com/lpryszcz/pyScaf

GenomeComp

Jit — Fri, 17 Feb 2017 08:38:32 -0600

GenomeComp is a tool for summarizing, parsing and visualizing the genome wide sequence comparison results derived from voluminous BLAST textual output, so as to locate the rearrangements, insertions or deletions of genome segments between species or strains.

It can be easily used to compare, parsing and visualize large genomic sequences, especially closely related genomes such as inter-species or inter-strains. In addition, it can also show other sequence features like repeat sequence distributions in one whole-genome DNA sequence by comparing the genome to itself.

It is a stand-alone graphical user interface (GUI) program which runs on Linux, Unix, Mac OS X (tested on version 10.2.4 only) and Microsoft Windows platforms and is written in Perl/Tk.

Address of the bookmark: http://www.mgc.ac.cn/GenomeComp/

HTSlib

Jit — Wed, 15 Mar 2017 11:38:05 -0500

Samtools is a suite of programs for interacting with high-throughput sequencing data. It consists of three separate repositories:

Samtools: Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format
BCFtools: Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants
HTSlib: A C library for reading/writing high-throughput sequencing data

Samtools and BCFtools both use HTSlib internally, but these source packages contain their own copies of htslib so they can be built independently.

Address of the bookmark: http://www.htslib.org/

ChromHMM: Chromatin state discovery and characterization

Abhimanyu Singh — Wed, 19 Apr 2017 04:06:23 -0500

ChromHMM is software for learning and characterizing chromatin states. ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of various histone modifications to discover de novo the major re-occuring combinatorial and spatial patterns of marks. ChromHMM is based on a multivariate Hidden Markov Model that explicitly models the presence or absence of each chromatin mark. The resulting model can then be used to systematically annotate a genome in one or more cell types. By automatically computing state enrichments for large-scale functional and annotation datasets ChromHMM facilitates the biological characterization of each state. ChromHMM also produces files with genome-wide maps of chromatin state annotations that can be directly visualized in a genome browser.

Address of the bookmark: http://compbio.mit.edu/ChromHMM/

NGS course Medical Genomics, scheduled for 17-20 September 2013 in UZ Leuven (Belgium).

Poonam Mahapatra — Mon, 12 Aug 2013 12:08:24 -0500

This course is open to all students and postdocs and registration for all academic participants is free of charge. To help us in organizing the course, please register online via http://gc.uzleuven.be where the preliminary program is also available.

This course is organized with support from the IAP “Belgian Medical Genomics Initiative”, SymBioSys and the Genomics Core.

For inquiries, please email Ms Narcisse Opdekamp ( narcisse.opdekamp@uzleuven.be ).

More at >> http://gc.uzleuven.be/

Bioinformatics Training Courses At RASA LSI

RASA Life Sciences — Wed, 06 Nov 2019 00:30:51 -0600

RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as Bioinformatics course, In silico Drug Discovery course, Next Generation Sequence data analysis course, Molecular Biology & Life science software development course wherein you learn from industry leaders how to apply these skills in life science & have a command over software developing process by using various methodologies. We conduct in-class training and instructor-led live online classes worldwide, along with corporate and skill development training worldwide.

Workshops are conducted in regular intervals on Drug Designing, Protein Modeling and Simulation, Chemoinformatics, Bioinformatics etc.The workshops are highly beneficial for working professionals, students, researcher for enhancements of the skills in short duration.