BOL: Related items

UPGMA Worked Example

Abhi — Wed, 13 Oct 2021 06:13:34 -0500

The tabs below include a walkthrough of clustering 7 biological sequences (A-G) using the Unweighted Pair-Group Method with Arithmetic mean (UPGMA) method. Note that UPGMA is actually a generic method and thus the walkthrough could apply to any objects A-G for which pairwise distances can be calculated. A small CGI site for generating a UPGMA tree from a distance matrix can be found here.

Address of the bookmark: http://www.slimsuite.unsw.edu.au/teaching/upgma/

TMRCA Calculator

BioStar — Wed, 03 Feb 2021 05:07:30 -0600

This program calculates the probability that two people have a certain number of generations between them, based on the standard infinite alleles formula of Walsh. It calculates both the probability of being at an exact number of generations back to the Most Recent Common Ancestor (MRCA) of a certain pair of people and the cumulative probability that the actual number of generations is less than a certain value. Note that the convention using generations is changed from an earlier version of this calculator which used "transmission events". It can list both result types in a table or graph. In either case the horizontal axis stops at the point where the cumulative probability reaches 95% or 10 generations, whichever is longer, or an absolute max of 50,000. Beyond 90% the calculation becomes inaccurate.

https://clandonaldusa.org/index.php/tmrca-calculator

Address of the bookmark: https://clandonaldusa.org/index.php/tmrca-calculator

chromoMap-An R package for Interactive visualization and mapping of human chromosomes

Rahul Nayak — Mon, 25 Jun 2018 17:22:24 -0500

chromoMap is an R package that provides interactive, configurable and elegant graphics visualization of the human chromosomes allowing users to map chromosome elements (like genes, SNPs etc.) on the chromosome plot. It introduces a special plot viz. the "chromosome heatmap" that, in addition to mapping elements, can visualize the data associated with chromosome elements (like gene expression) in the form of heat colors which can be highly advantageous in the scientific interpretations and research work. Because of the enormous size of the chromosomes, it is impractical to visualize each element on the same plot. But chromoMap plots provide a magnified view for each of chromosome location to render additional information and visualization specific for that location. You can map thousands of genes and can view all mappings easily. Users can investigate the detailed information about the mappings (like gene names or total genes mapped on a location) or can view the magnified single or double stranded view of the chromosome at a location showing each mapped element in sequential order (You will see in the demos below). Not ony that, the plots can be saved as HTML documents that can be customized and shared easily. In addition, you can include them in R Markdown or in R Shiny applications.

https://cran.r-project.org/web/packages/chromoMap/index.html

Interactive Bioinformatics Resources !

Jit — Thu, 12 Aug 2021 00:09:00 -0500

Learn how to use bioinformatics tools right from your browser.
Everything runs in a sandbox, so you can experiment all you want.

More at sandbox.bio

Address of the bookmark: http://sandbox.bio

S-plot2: creates an interactive, two-dimensional heatmap of sequences

Jit — Fri, 28 Sep 2018 05:36:19 -0500

S-plot2 creates an interactive, two-dimensional heatmap capturing the similarities and dissimilarities in nucleotide usage between genomic sequences (partial or complete). In S-plot2, whole eukaryotic chromosomes and smaller prokaryotic genomes can be efficiently compared. The tool includes functionality to extract, analyze, and automate BLAST queries of regions of interest within the heatmap. This facilitates the investigation of quickly evolving coding regions, novel coding regions, and laterally transferred elements.

http://www.putonti-lab.com/uploads/4/5/3/0/45307835/s-plot2_tutorial.pdf

http://journals.sagepub.com/doi/pdf/10.1177/1176934318797354

Address of the bookmark: https://bitbucket.org/lkalesinskas/splot

dotPlotly: Generate an interactive dot plot from mummer or minimap alignments

Rahul Nayak — Thu, 21 Feb 2019 10:22:17 -0600

Create an interactive dot plot from mummer output OR PAF format

R script that makes a plotly interactive and/or static (png/pdf) dot plot.

Shiny app available for testing

Address of the bookmark: https://github.com/tpoorten/dotPlotly

shinyChromosome:a GUI for the interactive creation of non-circular whole genome diagrams

Jit — Sat, 29 Feb 2020 00:39:50 -0600

shinyChromosome is a graphical user interface for interactive creation of non-circular whole genome diagrams developed using the R Shiny package.

To create single-genome plot by aligning genome data along all chromosomes of a single genome, go to the Single-genome plot menu.

To cretae two-genome plot for comparison of data across two genomes, go to the Two-genome plot menu.

For the detail format of input data, check the Input data format submenu of the Help menu.

shinyChromosome is deployed at http://150.109.59.144:3838/shinyChromosome/, http://shinyChromosome.ncpgr.cn, and https://yimingyu.shinyapps.io/shinyChromosome for online use. The source code and manual of shinyChromosome are freely available at https://github.com/venyao/shinyChromosome.

https://yimingyu.shinyapps.io/shinychromosome/

https://www.sciencedirect.com/science/article/pii/S1672022919301883

Address of the bookmark: https://yimingyu.shinyapps.io/shinychromosome/

Senior Bioinformatics Scientist @ Strand Life Sciences -- Bangalore, India

Wed, 02 Jan 2019 09:23:49 -0600

RESPONSIBILITIES
The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The candidate will be able to contribute to impactful work spanning patient care, clinical research, and new assay and method development.
REQUIREMENTS
A PhD in a quantitative field (statistics, math, bioinformatics, computer science, physics or similar) and work experience or post-doc experience handling high throughout genomics data.
PREFERENCES
Experience in working in inter-disciplinary groups and ability to author research publications are additional desired qualities.
LOCALE
The position is in Bangalore and reports to the Chief Scientific Officer.
HOW TO APPLY
Write to ramesh[at]strandls.com.

Life of a Bioinformatician !

Jitendra Narayan — Fri, 15 May 2026 02:30:08 -0500

Somewhere between FASTQ files, volcano plots, and 3 AM coffee… the gene is probably hiding too.

#Bioinformatics #Genomics #ResearchL

Tree illustrating the lack of interchromosomal rearrangement of the microchromosomes.

BioJoker — Mon, 26 Nov 2018 04:20:33 -0600

Tree illustrating the lack of interchromosomal rearrangement of the microchromosomes. No interchromosomal microchromosome fusions from the avian ancestor unless otherwise stated (macrochromosomal fusions not listed). The overall pattern of microchromosome stability and rearrangement across the species is illustrated

Jarvis et al. (2014)

Reference https://link.springer.com/article/10.1007/s00412-018-0685-6