BOL: Related items

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

Ideoplot

Shruti Paniwala — Mon, 13 Feb 2017 09:47:32 -0600

Simple ideogram plotting and annotation in R.

Basic usage:

Rscript Ideoplot.R --heatmap hm.bed --annotate annotations.bed --out ideogram.pdf
-or-
Rscript Ideoplot.R --annotate annotations.bed

Options
  --ideobed, i      A bed file of reference contig lengths/chromosome names
  --heatmap, -h     Fill chromosomes with normalized heatmap
                   (described below)
  --annotate, -a    Add character annotations.
  --out, -o         PDF output name.
  --stripes, -s     Specify a file containing the layout of the
                    annotations (description below)
  --bars, -b        Add track annotations
  --reference, -f   Either hg19, or hg38
  --topdown, r      Flag, when set, flips the orientation (P arms
                    drawn on top).

Address of the bookmark: https://github.com/mchaisso/Ideoplot

MinION_GC: An R script to do some QC on MinION data

Radha Agarkar — Sun, 03 Dec 2017 15:19:18 -0600

Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out there: it takes about a minute to analyse a 4GB flowcell on my laptop.

https://github.com/roblanf/minion_qc

Address of the bookmark: https://github.com/roblanf/minion_qc

Custom R charts coming to Excel !

Surabhi Chaudhary — Sat, 12 May 2018 07:30:28 -0500

This week at the BUILD conference, Microsoft announced that Power BI custom visuals will soon be available as charts with Excel. You'll be able to choose a range of data within an Excel workbook, and pass those data to one of the built-in Power BI custom visuals, or one you've created yourself using the API.

Since you can create Power BI custom visuals using R, that means you'll be able to design a custom R-based chart, and make it available to people using Excel — even if they don't know how to use R themselves. There also many pre-defined custom visuals available, including some familiar R charts like decision trees, calendar heatmaps, and hexbin scatterplots.

For more details on how you'll be able to use custom R visuals in Excel, check out the blog post linked below.

PowerBI Blog: Excel announces new data visualization capabilities with Power BI custom visuals

Applied Statistics for Bioinformatics using R

Neel — Thu, 30 Aug 2018 03:45:39 -0500

The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be introductory in explaining and programming elementary statistical concepts, thereby bridging the gap between high school levels and the specialized statistical literature

Retrieving Taxonomic Information with R

Rahul Nayak — Thu, 29 Aug 2019 01:38:39 -0500

This vignette will introduce users to the retrieval of taxonomic information with myTAI. The taxonomy() function implemented in myTAI relies on the powerful package taxize. Nevertheless, taxonomic information retrieval has been customized for the myTAI standard and for organism specific information retrieval.

Specifically, the taxonomy() function implemented in myTAI can be used to classify genomes according to phylogenetic classification into Phylostrata (Phylostratigraphy) or to retrieve species specific taxonomic information when performing Divergence Stratigraphy (see Introduction for details).

Address of the bookmark: https://cran.r-project.org/web/packages/myTAI/vignettes/Taxonomy.html

‘dockr’: the R container

Jit — Mon, 23 Dec 2019 09:56:49 -0600

dockr 0.8.6 is now available on CRAN. dockr is a minimal toolkit to build a lightweight Docker container image for your R package, in which the package itself is available. The Docker image seeks to mirror your R session as close as possible with respect to R specific dependencies. Both dependencies on CRAN R packages as well as local non-CRAN R packages will be included in the Docker container image.

If you want to know, how Docker works, and why you should consider using Docker, please take a look at the Docker website.

Address of the bookmark: https://www.docker.com/why-docker

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

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/