BOL: Related items

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

Github replacement !

Rahul Nayak — Thu, 26 Sep 2019 03:42:39 -0500

For a number of reasons researchers have been trying out GitLab as a replacement for for both GitHub and various continuous integration systems, and have been exploring configurations useful for model-fitting pipelines. Researchers turned one of these into an example repository that shows how to use GitLab together with the Rocker Docker images and the drake build system to reproducibly run a project pipeline, using the cacheing functionality across all three tools to make things reasonably speedy and enable both local and remote builds.

Check it out at https://gitlab.com/ecohealthalliance/drake-gitlab-docker-example.

Scientist Bioinformatics Positions

Thu, 30 Jan 2020 06:53:40 -0600

Bioinformatics-Multi_Omics_Integration

https://www.researchgate.net/job/939073_Senior_Scientist_Bioinformatics-Multi_Omics_Integration

Senior_Scientist_Bioinformatics-Transcriptomics_Analysis

https://www.researchgate.net/job/939075_Senior_Scientist_Bioinformatics-Transcriptomics_Analysis-Belgium_France_Switzerland_The_Netherlands

Senior Scientist Bioinformatics - Network Analytics

https://www.researchgate.net/job/939070_Senior_Scientist_Bioinformatics-Network_Analytics_Belgium_France_Switzerland_the_Netherlands

Team Leader Bioinformatics Data Sciences - Mechelen, Belgium

https://www.researchgate.net/job/938787_Team_Leader_Bioinformatics_Data_Sciences-Mechelen_Belgium

New Machine Learning Packages in R

Rahul Nayak — Fri, 27 Mar 2020 12:11:21 -0500

Machine Learning

autokeras v1.0.1: Implements an interface to AutoKeras, an open source software library for automated machine learning. See README for an example.

MTPS v0.1.9: Implements functions to predict simultaneous multiple outcomes based on revised stacking algorithms as described in Xing et al. (2019). See the vignette to get started.

quanteda.textmodels v0.9.1: Implements methods for scaling models and classifiers based on sparse matrix objects representing textual data. It includes implementations of the Laver et al. (2003) wordscores model, the Perry & Benoit’s (2017) class affinity scaling model, and the Slapin & Proksch (2008) wordfish model. See the vignette to get started.

SeqDetect v1.0.7: Implements the automaton model found in Krleža, Vrdoljak & Brčić (2019) to detect and process sequences. See the vignette for examples and theory.

studyStrap v1.0.0: Implements multi-Study Learning algorithms such as Merging, Study-Specific Ensembling (Trained-on-Observed-Studies Ensemble), the Study Strap, and the Covariate-Matched Study Strap. and offers over 20 similarity measures. See Kishida, et al. (2019) for background and the vignette for how to use the package.

R Shiny in Life Sciences – Top 7 Dashboard Examples

Neel — Fri, 01 Apr 2022 19:05:03 -0500

R Shiny is one of the easiest ways for developers to make production-ready dashboards when speed and functionality are crucial. Shiny is approachable with a lot of documentation available, and because of this, a lot of developers/researchers with non-coding backgrounds are able to produce some impressive results. The whole ecosystem is easy to get your head around and pretty much limitless with regard to what you can do.

Address of the bookmark: https://www.r-bloggers.com/2022/03/r-shiny-in-life-sciences-top-7-dashboard-examples/

SMASH: An alignment-free tool to find and visualise rearrangements between pairs of DNA sequences

Jit — Thu, 21 Dec 2017 08:26:57 -0600

SMASH is a completely alignment-free method to find and visualise rearrangements between pairs of DNA sequences. The detection is based on relative compression, namely using a FCM, also known as Markov model, of high context order (typically 20). The method has been approached with a tool (also called SMASH). For visualization, SMASH outputs a SVG image, with an ideogram output architecture, where the patterns are represented with several HSV values (only value varies). The following image, illustrating the information maps between human and chimpanzee for the several chromosomes, depicts an example:

Address of the bookmark: https://github.com/pratas/smash

Des Higgins: Visualizing Multiple Sequence Alignments

Wed, 26 Feb 2014 00:50:08 -0600

Copyright Broad Institute, 2013. All rights reserved. Des Higgins (http://www.bioinf.ucd.ie) gives a very entertaining introduction to the visualization of multiple sequence alignment, and to his widely-used Clustal tool. He highlights the emerging challenge of managing alignments with a very large number of sequences, and presents several approaches to this challenge, including faster algorithms and abstract views of clusters of alignments. This talk was presented at VIZBI 2011, an international conference series on visualizing biological data (http://www.vizbi.org) funded by NIH & EMBO. For information about data visualization efforts at the Broad Institute, please visit: http://www.broadinstitute.org/node/1363/