BOL: Related items

Trelliscope: flexibly visualize large, complex data in great detail from within the R statistical programming environment.

Jit — Tue, 21 Jan 2020 04:22:49 -0600

Trelliscope provides a way to flexibly visualize large, complex data in great detail from within the R statistical programming environment. Trelliscope is a component in the DeltaRho environment.

For those familiar with Trellis Display, faceting in ggplot, or the notion of small multiples, Trelliscope provides a scalable way to break a set of data into pieces, apply a plot method to each piece, and then arrange those plots in a grid and interactively sort, filter, and query panels of the display based on metrics of interest. With Trelliscope, we are able to create multipanel displays on data with a very large number of subsets and view them in an interactive and meaningful way.

Address of the bookmark: http://deltarho.org/docs-trelliscope/#introduction

Post Doc Computational Biology, Bioinformatics - Network Biology & Data Science, NGS (m/f/d)

Sat, 15 Feb 2020 06:13:35 -0600

https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential

GeneMates: an R package for Detecting Horizontal Gene Co-transfer between Bacteria Using Gene-gene Associations Controlled for Population Structure

Rahul Nayak — Sat, 07 Mar 2020 05:52:20 -0600

GeneMates is an R package implementing a network approach to identify horizontal gene co-transfer (HGcoT) between bacteria using whole-genome sequencing (WGS) data. It is particularly useful for investigating intra-species HGcoT, where presence-absence status of acquired genes is usually confounded by bacterial population structure due to clonal reproduction.

https://www.biorxiv.org/content/10.1101/2020.02.29.970970v1

Address of the bookmark: https://github.com/wanyuac/GeneMates

CRBHits: From Conditional Reciprocal Best Hits to Codon Alignments and Ka/Ks in R

Shruti Paniwala — Wed, 11 Nov 2020 23:06:03 -0600

CRBHits is a coding sequence (CDS) analysis pipeline in R (R Core Team, 2019). It reimplements the Conditional Reciprocal Best Hit (CRBH) algorithm crb-blast and covers all necessary steps from sequence similarity searches, codon alignments to Ka/Ks calculations and synteny. The new R package targets ecology, population and evolutionary biologists working in the field of comparative genomics.

Address of the bookmark: https://gitlab.gwdg.de/mpievolbio-it/crbhits

Powerful books for learning data analysis with R

LEGE — Tue, 28 May 2024 07:42:56 -0500

R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R today:

https://csgillespie.github.io/efficientR/

https://r-graphics.org/

https://rstudio-education.github.io/hopr/

https://r-pkgs.org/

https://r4ds.had.co.nz/

Address of the bookmark: https://r-graphics.org/

Modern Statistics with R

LEGE — Thu, 22 Aug 2024 04:44:06 -0500

This is the online version of the second edition of Modern Statistics with R. It is free to use, and always will be. Printed copies are available from CRC Press.

Live online courses on statistics with R based on this book, led by the author, are offered regularly; see this page for more information and dates.

The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you:

Data wrangling - importing, formatting, reshaping, merging, and filtering data in R.
Exploratory data analysis - using visualisations and multivariate techniques to explore datasets.
Statistical inference - modern methods for testing hypotheses and computing confidence intervals.
Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting.
Simulation - using simulation techniques for sample size computations and evaluations of statistical methods.
Ethics in statistics - ethical issues and good statistical practice.
R programming - writing code that is fast, readable, and (hopefully!) free from bugs.

The book includes plenty of examples and more than 200 exercises with worked solutions. The datasets used for the examples and the exercises can be downloaded here.

Address of the bookmark: https://www.modernstatisticswithr.com/

Orione – a web-based framework for NGS analysis in microbiology

Martin Jones — Wed, 23 Jul 2014 06:43:03 -0500

End-to-end NGS microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult due to a lack of interoperability, reproducibility, and transparency. To overcome these limitations researchers at CRS4, Italy have developed Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for NGS microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics.

Reference

Cuccuru G1, Orsini M, Pinna A, Sbardellati A, Soranzo N, Travaglione A, Uva P, Zanetti G, Fotia G. (2014) Orione, a web-based framework for NGS analysis in microbiology. Bioinformatics [Epub ahead of print]. [article]

Address of the bookmark: http://orione.crs4.it/

PhyloGrapher - Graph Visualization Tool

Jitendra Prajapati — Wed, 06 Apr 2016 19:06:48 -0500

PhyloGrapher is a program designed to visualize and study evolutionary relationships within families of homologous genes or proteins (elements).PhyloGrapher is a drawing tool that generates custom graphs for a given set of elements. In general, it is possible to use PhyloGrapher to visualize any type of relations between elements.

More at http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

Address of the bookmark: http://www.atgc.org/PhyloGrapher/PhyloGrapher_Welcome.html

Blobsplorer

Jit — Tue, 14 Jun 2016 10:28:58 -0500

Blobsplorer is a tool for interactive visualization of assembled DNA sequence data ("contigs") derived from (often unintentionally) mixed-species pools. It allows the simultaneous display of GC content, coverage, and taxonomic annotation for collections of contigs with a view to separating out those belonging to different taxa.

Blobsplorer is unlikely to be of use on its own as it requires contig data to be supplied in a format that involves considerable preprocessing (see below for a description). The easiest way to use Blobsplorer is as part of a workflow using scripts from here.

Address of the bookmark: http://nematodes.org/martin/blobsplorer/blobsplorer.html

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