Survival analysis with TCGA data in R | Create Kaplan-Meier Curves

In this video I talk about the concept of survival analysis, what questions does it help to answer and what data do we need to perform this analysis. I also discuss important concepts like censoring and how it is perform and explain how to interpret Kaplan-Meier curves. Lastly, I demonstrate how to perform survival analysis in R using survival and survminer packages. I hope you find this video helpful! Leave your thoughts in the comment section below! Link to Code: github.com/kpatel427/YouTubeTutorials/blob/main/KM… How to download data from GDC portal?    • Download data from GDC Portal using T...   How to convert gene IDs to symbols?    • 3 ways to convert Ensembl IDs to gene...   Chapters: 0:00 Intro 0:35 Intuition behind survival analysis 2:21 Why do we perform survival analysis? 3:57 What is Censoring and why is it important? 6:14 What is considered as an event? 6:35 Methods for survival analysis 8:03 How to read a Kaplan-Meier curve? 10:31 Question to answer using survival analysis 10:53 3 things required for survival analysis 12:08 Download clinical data from GDC portal 15:57 Getting status information and censoring data 17:31 Set up an “overall survival” (i.e. time) for each patient in the cohort 19:01 For event/strata information for each patient, fetch gene expression data from GDC portal 19:33 Build query using GDCquery() 22:45 Download data using GDCdownload() 23:14 Extract counts using GDCprepare() 25:07 Perform Variance Stabilization Transformation (vst) on counts before further analysis 27:38 Wrangle data to get the relevant data and data in the right shape 33:11 Approaches to divide cohort into 2 groups based on expression 34:41 Bifurcating patients into low and high TP53 expression groups 34:57 Define strata for each patient 38:41 Compute a survival curve using survfit() and creating a Kaplan-Meier curve using ggsruvplot() 41:30 survfit() vs survdiff() You can show your support and encouragement by buying me a coffee: www.buymeacoffee.com/bioinformagic To get in touch: Website: bioinformagician.org/ Github: github.com/kpatel427 Email: [email protected] #bioinformagician #bioinformatics #survival #survminer #survivalanalysis #kaplanmeier #tcga #gdcportal #tcgaportal #nci #cran #bioconductor #funcotator #variantcalling #variants #gatk #vcf #gvcf #haplotype #alleles #geneticvariants #mutations #gff3 #gff #gtf #sam #bam #phred #fasta #fastq #singlecell #10X #ensembl #biomart #annotationdbi #annotables #affymetrix #microarray #affy #ncbi #genomics #beginners #tutorial #howto #omics #research #biology #GEO #rnaseq #ngs