In 1997, Thomas Wang introduced an integer hash function using some techniques invented by Bob Jenkins. The inverted version of this hash was then introduced by Geoffrey Irving.
This hash function found his way to bioinformatics through Heng Li which used it in miniasm and minimap.
Pandey et al., further used it also to make the counting quotient filter exact in squeakr.
Beside work from Jean-Pierre Both, this function have not been explored in Rust albeit to the best of my knowledge.
Drawing map of a country with indications of cities, samples are now common tasks in R. But what about adding to such a map, neighboring countries? Here we go.
We will draw a map of Ivory Coast with its neighboring countries.
Let us first load the libraries:
library(tmap) # to draw the map library(tibble) # for sites table creation library(sf) library(maptools) library(rgeos) library(raster) # to download data Then, let us create a tibble with the coordinates of our locations:
There is multiple way to export images in R, but the one I prefer is with the package Cairo. Cairo, gives controls on the properties of the final image and such control is always appreciated especially if you’re planning to submit images in a scientific publication like it’s often the case for me.
First if you haven’t yet installed Cairo, install it from CRAN with:
install.packages('Cairo') After that let us create a plot for our example:
I was late testing Reticulate and how it harnesses Python in R, but I was not deceived. The fact that you can seamlessly work in python inside Rstudio amazed me. I have found some features Rstudio give who are really amazing. Here is the list.
1. The possibility to execute a chunk of python code with Ctrl + enter like with R As with R code when you have a Python script file, you can execute part of the code using RStudio shortcut like Ctrl + Enter.
Microbial analysis using amplicon genes is a good field for data analysis. The fact that microbes are ubiquitous in our environments and that high throughput sequencing causes a data deluge are the main causes.
Crucial steps in microbial analysis are primers removing, demultiplexing, filtering and trimming of sequences, fitting of error models, sequences clustering and taxonomic assignment.
Among above steps sequences clustering and taxonomic assignments appears as the most challenging. Sequences clustering, aims to reduce inherent PCR and DNA sequencing errors.
Context It came to my mind to write this short post to put emphasis on the importance for people to share it. It became a need for me to ouline this point because of the reality that best mind are not always willing to share knowledge, sometimes because they don’t see the importance of teachnig. And this fact limit our true power and evolution as a community.
Why It’s important to teach because teaching prove to yourself that you master the subject (at a certain level at least).
Since February 26 i am working at Seedstars Ivory Coast in a venture named Bora digital who works mostly in marketing and digital marketing.
From a first background of agronomy (my Bsc) to bioinformatics (my master), at each step i have faced surprises, questions and oppositions from peoples around me.
How do you did it? Why are you know working in marketings ? Why are you not as your peers working in farms or at least pursuing bioinformatics studies?
“R is not just a programming language, but it is also an interactive environment for doing data science.”
“Investing a little time in learning R each day will pay off handsomely in the long run."—
Hadley Wickham and Garret Grolemund in R for Data Science.
When i have heard for the first time about R, i was a student in Bsc in agronomy in Ivory Coast. My professor of statistics just told me that R was great comparing to other statistical software and gave me the link to the site of the comprehensive R archive network.