Since 2020 we have also been uploading videos to YouTube and our meeting schedule is public. We have a Google Group that is reserved to our members. If you have suggestions for future sesssions, please let us know!.
We would love feedback from the community and hope that our blog posts and videos will help researchers at LIBD and elsewhere. There are many packages and functions we don’t know about, plus the R community is always growing. This is part of our efforts to continue learning about R.
By Sang Ho Kwon. Recent advancements in spatially-resolved transcriptomics (SRT) technologies have ushered in a new era of possibilities for biological research. These technologies offer the unique ability to map biomolecular information within the native tissue architecture. Preserving the spatial resolution of genome-wide gene expression allows researchers to obtain a more holistic view of the tissue microenvironment, particularly the underlying molecular and cellular dynamics in a spatial-anatomical context, which is useful to understand the composition, states, and function of individual cell types, as well as their interactions with one another in a defined microenvironment.
By Nick Eagles Over the past few years, I’ve had the opportunity to work with a lot of whole-genome bisulfite-sequencing (WGBS) datasets. They provide a powerful opportunity to look at DNA methylation on a complete scale, in contrast to microarrays which target a narrower set of important CpG sites across the genome. But for this same reason, the data is often unwieldy, and can feel difficult to tackle even with access to powerful computational resources.
By Nick Eagles We’ve recently been interested in exploring the (largely python-based) tools others have published to process spatial transcriptomics data for various end goals. A common goal is to integrate data from platforms like Visium, which provides some information about how gene expression is spatially organized, with other approaches with potentially better spatial resolution or gene throughput. In particular, we came across a paper by Biancalani, Scalia et al.
By Arta Seyedian Medical Cost Personal Datasets Insurance Forecast by using Linear Regression Link to Kaggle Page Link to GitHub Source Around the end of October 2020, I attended the Open Data Science Conference primarily for the workshops and training sessions that were offered. The first workshop I attended was a demonstration by Jared Lander on how to implement machine learning methods in R using a new package named tidymodels.
By Brenda Pardo A month ago, I started an enriching adventure by joining Leonardo Collado-Torres’ team at Lieber Institute for Brain Development. Since then, I have been working on modifying spatialLIBD, a package to interactively visualize the LIBD human dorsolateral pre-frontal cortex (DLPFC) spatial transcriptomics data (Maynard, Collado-Torres, Weber, Uytingco, et al., 2020). The performed modifications allow spatialLIBD to use objects of the VisiumExperiment class, which is designed to specifically store spatial transcriptomics data (Righelli and Risso, 2020).
We recognize that our code of conduct is outdated. We now also follow the Bioconductor Project Code of Conduct, so please read that one first. Thank you!
The LIBD rstats club is committed to providing a welcoming and harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of website participants in any form. Sexual language and imagery is not appropriate for any venue related to this website, including blog posts, talks, workshops, parties, Twitter and other online media. Website participants violating these rules may be sanctioned or expelled from the website at the discretion of the LIBD rstats club members.
This code of conduct applies to all participants, including LIBD rstats club members and applies to all modes of interaction, both in-person and online, including LieberInstitute GitHub project repos, the LIBD rstats club comments section, Slack channels and Twitter.
LIBD rstats club participants agree to:
If any participant engages in harassing behavior, the LIBD rstats club organizers may take any lawful action we deem appropriate, including but not limited to warning the offender or asking the offender to leave the website. (If you feel you have been unfairly accused of violating this code of conduct, you should contact the LIBD rstats club organizers with a concise description of your grievance.)
The above text has been modified from the rOpenSci 2018 unconference code of conduct, which in turn states that parts of the text are licensed CC BY-SA 4.0. Credit to SRCCON. Also inspired by the Ada Initiative’s “how to design a code of conduct for your community.”