BOL: Related items

Genome Informatics Section Lab !

Sat, 25 Jan 2020 06:38:23 -0600

Our section develops and applies computational methods for the analysis of massive genomics datasets, focusing on the challenges of genome sequencing and comparative genomics. We aim to improve such foundational processes and translate emerging genomic technologies into practice.

The Genome Informatics Section is hiring! Come join our outstanding team at the NIH’s National Human Genome Research Institute and contribute to the development of new reference genomes and computational methods for DNA sequencing and analysis. Both postdoc and PhD students positions are available. More information and application instructions follow below.

More at https://genomeinformatics.github.io/

MEGADOCK 4.0

Suleman Khan — Thu, 07 Aug 2014 18:08:54 -0500

An ultra–high-performance protein–protein docking software for heterogeneous supercomputers

Summary: The application of protein–protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of over 97% strong scaling.

Availability and Implementation: MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock.

Contact: akiyama@cs.titech.ac.jp

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2014/08/06/bioinformatics.btu532.short

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

Neel — Sun, 20 Dec 2020 01:39:54 -0600

The first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. SneakySnake greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short (Illumina) and long (ONT and PacBio) reads. Described by Alser et al. (preliminary version at https://arxiv.org/abs/1910.09020).

Address of the bookmark: https://github.com/CMU-SAFARI/SneakySnake

GrapheR !!!

John Parker — Thu, 14 Aug 2014 14:02:17 -0500

What a wonderful gem GrapheR is.... Oh yes it is. GrapheR is a GUI for base graphics in R by http://www.maximeherve.com/. The package provides a graphical user interface for creating base charts in R. It is ideal for beginners in R, as the user interface is very clear and the code is written along side into a text file, allowing users to recreate the charts directly in the console.

Adding and changing legends? Messing around with the plotting window settings? It is much easier/quicker with this GUI than reading the help file and trying to understand the various parameters.
Here is a little example using the iris data set.

library(GrapheR)
data(iris)
run.GrapheR()

This will bring up a window that helps me to create the chart and tweak the various parameters.

Finally, I find the underlying R code in a file created by GrapheR. For more details read also the package vignette, which is available in English, French and German!

OGDRAW - Draw Organelle Genome Maps

Abhi — Tue, 05 Oct 2021 03:34:35 -0500

OrganellarGenomeDRAW converts annotations in the GenBank or EMBL/ENA format into graphical maps. The input has to be a GenBank or EMBL/ENA flat file wherase the output can vary among several types of files. The application is optimized to create detailed high-quality maps of organellar genomes (plastid and mitochondria). Nevertheless, you can upload most database entries.

Please take a look at our FAQ section and do not hesitate to report bugs or suggestions for improvements by email.

Address of the bookmark: https://chlorobox.mpimp-golm.mpg.de/OGDraw.html

pybedtools

Shruti Paniwala — Wed, 20 Aug 2014 01:03:41 -0500

pybedtools is a Python wrapper for Aaron Quinlan's BEDtools programs (https://github.com/arq5x/bedtools), which are widely used for genomic interval manipulation or "genome algebra". pybedtools extends BEDTools by offering feature-level manipulations from with Python. See full online documentation, including installation instructions, at http://pythonhosted.org/pybedtools/.

More at http://pythonhosted.org/pybedtools/

A powerful toolset for genome arithmetic.http://code.google.com/p/bedtools/

HIV genome database !

Rahul Nayak — Fri, 21 Jan 2022 05:40:15 -0600

HIV resources

https://www.hiv.lanl.gov/components/sequence/HIV/search/search.html

Address of the bookmark: https://www.hiv.lanl.gov/components/sequence/HIV/search/search.html

Human Complete Genome

Shruti Paniwala — Wed, 06 Jul 2022 06:42:55 -0500

Telomere-to-telomere consortium

We have sequenced the CHM13hTERT human cell line with a number of technologies. Human genomic DNA was extracted from the cultured cell line. As the DNA is native, modified bases will be preserved. The data includes 30x PacBio HiFi, 120x coverage of Oxford Nanopore, 70x PacBio CLR, 50x 10X Genomics, as well as BioNano DLS and Arima Genomics HiC. Most raw data is available from this site, with the exception of the PacBio data which was generated by the University of Washington/PacBio and is available from NCBI SRA.

A UCSC browser is available for v2.0 (as well as legacy v1.0 and v1.1 versions). An interactive dotplot visualization of all genomic repeats is also available from resgen.io. Known issues identified in the assembly are tracked at CHM13 issues.

MORE at https://github.com/marbl/CHM13

Address of the bookmark: https://www.science.org/doi/10.1126/science.abj6987

Bioinformatics JRF/SRF position at IARI

Thu, 04 Sep 2014 04:14:01 -0500

DIVISION OF NEMATOLOGY
INDIAN AGRICULTURAL RESEARCH INSTITUTE
NEW DELHI 110012
Applications are invited for the posts of one Junior
Research Fellow and one RA in the DBT funded project entitled “ Plant parasitic nematode genome informatics - insilico resource development”. The project is for a period of three years.

Essential qualifications for JRF
: M. Sc. in Bioinformatics with experience in Proteomics, genomics and structural biology. Knowledge of programming language, pearl and database – HTML, CSS,php and Java script.
Essential qualifications for Research Associate:
MSc/MTech in Bioinformatics with three years experience or Ph.D in Bioinformatics with experience in proteomics, genomics and structural biology. Knowledge of programming language, perl and database
– HTML, CSS, Java script. NGS sequence assembly and analysis and algorithm designing.
Age limit : 35 years maximum (5 year relaxation for SC/ST and women candidates)
Emoluments:
JRF: 16,000 + 30% HRA
.
Res Assoc: Rs22,000 + 30% HRA
The post is purely temporary in nature and is co-terminus with the project. The appointment would be initially for one year and may be extended further upon satisfactory performance.
Interested candidates
should send the duly filled application forms (format in the following page ) so as to reach on or before 20.9.2014 along with all the relevant documents.

More at http://www.iari.res.in/files/JRF_RA-03092014-20140903-135319.pdf

Steps to find all the repeats in the genome !

Neel — Thu, 31 Aug 2023 02:43:28 -0500

To find repeats in a genome from 2 to 9 length using a Perl script, you can use the RepeatMasker tool with the "--length" option[0]. Here's a step-by-step guide:

Install RepeatMasker: First, you need to install RepeatMasker on your system. You can download it from the RepeatMasker website[0].

Prepare the genome sequence: Make sure you have the genome sequence in a FASTA file format. Let's assume the file is named "genome.fasta".

./RepeatMasker -pa -nolow -norna -no_is -div -lib RepeatMaskerLib.embl -gff -xsmall -small -poly -species -dir -length - genome.fasta

Replace the following placeholders with appropriate values:

: The number of processors/threads you want to use for parallel processing.
: The divergence value for the species you are analyzing. You can find divergence values for different species in the RepeatMasker documentation[0].
: The name of the species you are analyzing.
: The directory where you want the output files to be saved.
and : The minimum and maximum lengths of the repeats you want to find (in this case, 2 and 9).

Analyze the output: RepeatMasker will generate several output files, including a .out file. You can parse this file to extract the information you need. There is a Perl tool called "one_code_to_find_them_all.pl" that can help you parse RepeatMasker output files[0]. You can download it from the source provided.

Use the provided Perl script: Once you have the "one_code_to_find_them_all.pl" script, you can run it to conveniently parse the RepeatMasker output files. Here's an example of how to use it:

perl one_code_to_find_them_all.pl --rm --length

Replace with the path to your RepeatMasker .out file, and with the path to a file containing the lengths of the reference elements.

This script will generate several output files, including .log.txt and .copynumber.csv, which contain quantitative information about the identified repeat elements.

Remember to adjust the parameters and options according to your specific needs and the characteristics of your genome.