BOL: Related items

SeqCAT: Sequence Conversion and Analysis Toolbox

Neel — Fri, 14 Jun 2024 14:36:53 -0500

Your all-in-one solution for smooth conversion of sequence coordinates.

Designed for bioinformatics data analysis and daily laboratory work, SeqCAT simplifies sequence coordinate conversion. Extract gene and transcript information, manipulate sequences, and easily validate complex genetic events such as fusions with SeqCAT.

More at https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkae422/7683049?login=false

Address of the bookmark: https://mtb.bioinf.med.uni-goettingen.de/SeqCAT/home

poRe: an R package for the visualization and analysis of nanopore sequencing data

Jit — Thu, 23 Nov 2017 09:55:57 -0600

Motivation: The Oxford Nanopore MinION device represents a unique sequencing technology. As a mobile sequencing device powered by the USB port of a laptop, the MinION has huge potential applications. To enable these applications, the bioinformatics community will need to design and build a suite of tools specifically for MinION data.

Results: Here we present poRe, a package for R that enables users to manipulate, organize, summarize and visualize MinION nanopore sequencing data. As a package for R, poRe has been tested on Windows, Linux and MacOSX. Crucially, the Windows version allows users to analyse MinION data on the Windows laptop attached to the device.

Availability and implementation: poRe is released as a package for R at http://sourceforge.net/projects/rpore/ . A tutorial and further information are available at https://sourceforge.net/p/rpore/wiki/Home/

Contact:mick.watson@roslin.ed.ac.uk

Address of the bookmark: https://academic.oup.com/bioinformatics/article/31/1/114/2365693

BBMap help

Shruti Paniwala — Mon, 10 Oct 2016 06:29:03 -0500

BBMAP • a solution for everything

That content has been reformatted and it is being expanded to include more information.

There are common options for most BBMap suite programs and depending on the file extension the input/output format is automatically chosen/set.

Using BBMap

Mapping Nanopore reads

BBMap.sh has a length cap of 6kbp. Reads longer than this will be broken into 6kbp pieces and mapped independently.

More at https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html

Address of the bookmark: https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html

PGAP-X: Extension on pan-genome analysis pipeline

Rahul Nayak — Tue, 23 Jan 2018 11:41:43 -0600

PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different conservative levels, and genetic variation from pan-genome sight. At the same time, analytical result data from many other programs, including genome alignment result and orthologs clusters, are also supported to be further analyzed or visualized in PGAP-X. The workflow and feature snapshot in PGAP-X were shown as Fig.1 and Fig.2.

Address of the bookmark: https://pgapx.ybzhao.com/

Beagle

Jit — Thu, 27 Oct 2016 11:19:00 -0500

Beagle is a software package that performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection.

Beagle version 4.1 has a more accurate genotype phasing algorithm and a very fast and accurate genotype imputation algorithm. Version 4.1 also has several changes to the command line arguments which are described in the release notes. The "ped" argument has no effect in version 4.1. If your data contains nuclear families and you want to model the parent-offspring relationships when phasing genotypes, please use version 4.0.

If you use Beagle 4.1 in a published analysis, please report the program version and cite the appropriate article.

The citation for Beagle's phasing algorithm is:

S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097.doi:10.1086/521987

The citation for Beagle's genotype imputation algorithm is:

B L Browning and S R Browning (2016). Genotype imputation with millions of reference samples. Am J Hum Genet 98:116-126.doi:10.1016/j.ajhg.2015.11.020

The citation for Beagle's IBD detection algorithm is:

B L Browning and S R Browning (2013). Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194(2):459-71.doi:10.1534/genetics.113.150029

Address of the bookmark: http://faculty.washington.edu/browning/beagle/beagle.html

bpRNA: large-scale automated annotation and analysis of RNA secondary structure

Rahul Nayak — Wed, 23 May 2018 03:24:33 -0500

bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature.

The bpRNA code is written in perl and requires the Graph perl module. Several additional scripts for analysis are included. The source code is available at http://github.com/hendrixlab/bpRNA.

Address of the bookmark: http://github.com/hendrixlab/bpRNA

Statistics Using R with Biological Examples

Neel — Thu, 03 Nov 2016 04:55:41 -0500

This book is a manifestation of my desire to teach researchers in biology a bit more about statistics than an ordinary introductory course covers and to introduce the utilization of R as a tool for analyzing their data. My goal is to reach those with little or no training in higher level statistics so that they can do more of their own data analysis, communicate more with statisticians, and appreciate the great potential statistics has to offer as a tool to answer biological questions.

This is necessary in light of the increasing use of higher level statistics in biomedical research. I hope it accomplishes this mission and encourage its free distribution and use as a course text or supplement.

K Seefeld, May 2007

Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees

Rahul Nayak — Wed, 27 Nov 2019 05:32:33 -0600

The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also supported).

Other tools

https://github.com/shenwei356/taxonkit

ETE, version: 3.1.1
BioPython, version: 1.73
taxadb, version: 0.10.1
TaxonKit, version: 0.5.0

Address of the bookmark: https://pypi.org/project/ete3/3.1.1/

Junior Research Fellow at Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram

Mon, 07 Nov 2016 10:27:06 -0600

Adv. # 22/ 2016
Applications are invited from suitable candidates for one position of Junior Research Fellow in a DST funded bioinformatics research project entitled "Major gene influxes in microbial genome evolution" in the Laboratory of Dr. Shijulal Nelson-Sathi at Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram.

ESSENTIAL QUALIFICATIONS:
We are looking for a motivated candidate with keen interest in bioinformatics and microbial genome evolution. The candidate must have a Master’s Degree in Bioinformatics, Computational Biology, Computer Science, Microbiology, Biology or a related field with good academic record.

DESIRABLE QUALIFICATIONS
Hands on research experience on handling next generation sequencing data and phylogenetic reconstruction methods. Excellent programming skills (Perl/Python/Java/Php) and experience in working on Unix/Linux platform is preferred. Furthermore; good knowledge is required in statistics (R/Matlab) and the application of bioinformatics analysis tools.

AGE:
Below 28 years as on 15th November, 2016.

EMOLUMENTS:
Rs. 25,000 + 20% HRA for NET/GATE qualified and Post Graduate in Professional Degree course qualified candidates and
Rs. 12,000/- + 20% HRA for others.

DURATION:
Initial appointment will be given for one year and further extension will be based on the performance till termination of the project.
Only those fulfilling the above criteria need apply and will be called for interview. In the event of more than 10 candidates being short-listed by screening the applications, a written test will be conducted before the selection interview and only those who are successful in the written test will be interviewed. No TA/ DA will be given for appearing in the interview.

Suitably qualified candidates may send applications in the prescribed format (Download here) with a photograph, a copy of full resume indicating the percentage of Marks obtained and attested photocopies of credentials & experience to reach the undersigned on or before 15th November, 2016. Envelopes must be superscripted with abbreviated title of the project, advertisement number and job title. Selection to the position will not entitle the candidate to any future positions at RGCB (permanent or otherwise). As with all project positions at RGCB, the position will be co terminus with end of the project.

netGO: R-Shiny package for network-integrated pathway enrichment analysis

Jit — Wed, 12 Feb 2020 12:40:54 -0600

netGO is an R/Shiny package for network-integrated pathway enrichment analysis.
netGO provides user-interactive visualization of enrichment analysis results and related networks.

Currently, netGO supports analysis for four species (Human, Mouse, Arabidopsis thaliana,and Yeast)
These data are available from netGO-Data repository.

https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa077/5728635

Address of the bookmark: https://github.com/unistbig/netGO