Education
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My regret is not learning linear algebra well during college.
I barely passed the exam for it (and calculus, it was a nightmare :) ).
To be fair..
It was not taught well and it sounded too boring. I did not know what the application of matrix multiplication was, not until…
Many years later, I started to learn bioinformatics.
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Understand CCA Following my last blog post on PCA projection and cell label transfer, we are going to talk about CCA.
In single-cell RNA-seq data integration using Canonical Correlation Analysis (CCA), we typically align two matrices representing different datasets, where both datasets have the same set of genes but different numbers of cells.
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Understand the example datasets We will use PBMC3k and PBMC10k data. We will project the PBMC3k data to the PBMC10k data and get the labels
library(Seurat) library(Matrix) library(irlba) # For PCA library(RcppAnnoy) # For fast nearest neighbor search library(dplyr) # Assuming the PBMC datasets (3k and 10k) are already normalized # and represented as sparse matrices # devtools::install_github('satijalab/seurat-data') library(SeuratData) #AvailableData() #InstallData("pbmc3k") pbmc3k<-UpdateSeuratObject(pbmc3k) pbmc3k@meta.
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Motivation What’s the most common problem you need to solve when dealing with genomics data?
For me, it is Genomic Intervals!
The genomics data usually represents linearly: chromosome name, start and end.
We use it to define a region in the genome ( A peak from ChIP-seq data); the location of a gene, a DNA methylation site ( a single point), a mutation call (a single point), and a duplication region in cancer etc.
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I have been writing blog posts for over 10 years. I was using blogspot and in 2018, I switched to blogdown and I love it.
My blogdown website divingintogeneticsandgenomics.com was using Hugo v0.42 and blogdown v1.0. It has been many years and now I have a macbook pro with an M3 chip. I could not install the old versions of the R packages to serve the site.
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If you apply for a Bioinformatics position, hundreds of CVs get to sent to the hiring manager. How to stand out among all of them? Below are 6 tips from my hiring experience:
Include a GitHub Link: Ensure your CV has a GitHub link with relevant content like Python or R packages, data analysis projects, or replicated figures from published papers.