Shankar K Shakya Ph.D.

Abstract done for #PAG32. If you are interested working in ornamental industry, come find me at the trees and shrubs session on day1.

Our Petunia hybrida genome paper is now on @biorxivpreprint. This was a collaborative project between @BallHort @Ball_Helix and Plant & Food research group of New Zealand. biorxiv.org/content/10.110…

The 10 types of clustering that all data scientists need to know. Let's dive in: 1. K-Means Clustering: This is a centroid-based algorithm, where the goal is to minimize the sum of distances between points and their respective cluster centroid. 2. Hierarchical Clustering: This method creates a tree of clusters. It is subdivided into Agglomerative (bottom-up approach) and Divisive (top-down approach). 3. DBSCAN (Density-Based Spatial Clustering of Applications with Noise): This algorithm defines clusters as areas of high density separated by areas of low density. 4. Mean Shift Clustering: It is a centroid-based algorithm, which updates candidates for centroids to be the mean of points within a given region. 5. Gaussian Mixture Models (GMM): This method uses a probabilistic model to represent the presence of subpopulations within an overall population without requiring to assign each data point to a cluster. 6. Spectral Clustering: It uses the eigenvalues of a similarity matrix to reduce dimensionality before applying a clustering algorithm, typically K-means. 7. OPTICS (Ordering Points To Identify the Clustering Structure): Similar to DBSCAN, but creates a reachability plot to determine clustering structure. 8. Affinity Propagation: It sends messages between pairs of samples until a set of exemplars and corresponding clusters gradually emerges. 9. BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies): Designed for large datasets, it incrementally and dynamically clusters incoming multi-dimensional metric data points. 10. CURE (Clustering Using Representatives): It identifies clusters by shrinking each cluster to a certain number of representative points rather than the centroid. There you have it- my top 10 types of clustering every data scientist needs to know. The next problem you'll face is how to apply them to data science to business. I'd like to help. I’ve spent 100 hours consolidating my learnings into a free 5-day course, How to Solve Business Problems with Data Science. It comes with: 300+ lines of R and Python code 5 bonus trainings 2 systematic frameworks 1 complete roadmap to avoid mistakes and start solving business problems with data science, TODAY. 👉 Here it is for free: learn.business-science.io/free-solve-bus…

FLAIR2: Detecting haplotype-specific transcript variation in long reads genomebiology.biomedcentral.com/articles/10.11…

Two papers in @Nature present a new genome editing technique that enables the insertion, inversion and deletion of long DNA sequences at user-specified genome positions. The approach may provide an easier method of genome editing. go.nature.com/3RGkI8M go.nature.com/3RHBvIs

Generalized linear mixed models (GLMMs) are critically important for the analysis of non-normal data. Check out our recent review article to learn more. frontiersin.org/journals/horti…

Genome assembly Tutorials with SPades- Paired-end Illumina Reads

Attending summer institute of statistical genetics at @KendedaBuilding @GeorgiaTech this week. Any twitter friends around here!!!

Krisp: A Python package to aid in the design of CRISPR and amplification-based diagnostic assays from WGS data journals.plos.org/ploscompbiol/a… 🧬🖥️ github.com/grunwaldlab/kr… 🐍 pypi.org/project/krisp/

We are excited to announce cleaner nucleotide (nt) and protein (nr) BLAST databases with more accurate results! We now use NCBI quality assurance tools to systematically remove misleading sequences. Learn more: ow.ly/CEk950RlpoM #NCBICGR

@aeharkess Thank you @aeharkess. Do you think producing 5 gfa files (one per each flowcell of data) and merging them to produce 1 gfa and then converting to 1 assembly file will work if I dont want to use 1tb of RAM. Thoughts??

@shakya if it’s anything like octoploid dahlia, the easiest solution then would be to spin up an AWS node with 1tb of ram.

HiFi assembler folks, if you have tons of raw fasta (total 700Gb) files as input but limited by the RAM whats the path you have taken to perform an assembly. Asking for a friend.

@aeharkess probably around 8-9Gb, 40x converage

@shakya what’s the genome size and ploidy and hifi coverage?

REVIEW: Reflections on the ABC model of flower development (John L Bowman, Edwige Moyroud) buff.ly/3OIDlHM @ASPB #PlantSci

Why?

Want to learn about the latest updates we've made to enhance the options available when you're using the custom annotation option in the Variant Effect Predictor? Read more in our latest blog post: 👉 ensembl.info/2024/01/26/coo… #genomics #bioinformatics #VEP 🧬

BCFtools/liftover: bcftools plugin to convert genetic variants across genome assemblies academic.oup.com/bioinformatics… 🧬🖥️ #liftover-vcfs" target="_blank" rel="nofollow noopener">github.com/freeseek/score…

@polyploidtools I missed it this year.

That's the end of day one for this year's polyploid meeting! Thank you and everyone who participated or presented. We'll see you again at 8:30 tomorrow morning!

@krishnabhatarai @TAMU @AgriLife @tamuhort congrats

I am happy to share that I have joined Department of Horticultural Sciences, Texas A&M University and Texas A&M AgriLife Research and Extension Center - Dallas as Assistant Professor, Controlled Environment Breeder @TAMU @AgriLife @tamuhort

🧑‍💻 Happy to announce that sandbox.bio v2 has been released! Same bioinformatics tutorials, but now powered by Linux running in your browser. Stay tuned, we'll be adding lots more tutorials this year.