Видео 98
Просмотров 34 799

Plotting TPM values - while learning how to melt data (John Rinn Computational Genomics Lab)

31:29

GGPLOT (III) Getting familiar with all layers of GGPLOT! (John Rinn Computational Genomics Lab)

20:06

GGPLOT II : Going deeper into analysis and figure making (John Rinn Computational Genomics Lab)

20:08

Making RNAseq FIgures ! (John Rinn Computational Genomics)

18:15

One script to run all the RNAseq Analyses (John Rinn Computational Genomics Lab)

6:38

Let's analyze our RNAseq data in TPM (transcripts per million). John Rinn Computational Genomics Lab

30:50

Custom Function Bonus - making plots with one line of code! (John Rinn Computational Genomics Lab)

From the last lesson we can see that we would repeat a lot of steps to make our TPM or log2 fold change plots with RNAseq data. Whenever, this is the case it's time to make a custom function ! Here we will do just that and you can now make figures with one line of code !!
John Rinn Github for this class:
github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/07_visualization_figures/04_TPM_plots.Rmd
-- see the bottom half of the .RMD for how to make custom functions
John Rinn CGL Website for this class:
www.lncrna.io/cgl-level-7
-TPM Plots
John Rinn BioFrontiers:
www.colorado.edu/biofrontiers/john-rinn
John Rinn Lab:
lncRNA.io
John Rinn Teaching:
lncrna.io/teaching
John Rinn University of Colorado ...

Видео

Plotting TPM values - while learning how to melt data (John Rinn Computational Genomics Lab)

31:29

Plotting TPM values - while learning how to melt data (John Rinn Computational Genomics Lab)

Просмотров 76Месяц назад

Let's find out how much genes changed in abundance (TPMs) during the treatment of Dox. We will also learn a key skill of pivoting data tables in R. This allows us to group by conditions and get average and standard deviation (error) from our replicates across time ! It's a bit tricky to get your head around at first (at least it was/still is for me). But absolutely a key concept to learn in R a...

GGPLOT (III) Getting familiar with all layers of GGPLOT! (John Rinn Computational Genomics Lab)

20:06

GGPLOT (III) Getting familiar with all layers of GGPLOT! (John Rinn Computational Genomics Lab)

Просмотров 28Месяц назад

This is our final lesson in GGPLOT-ology. We will make some interesting figures and show some tricks to make lots of figures fast ! John Rinn Github: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/07_visualization_figures/02_plotting_ggplot_2.Rmd John Rinn CGL Website for this class: www.lncrna.io/cgl-level-7 -GGPLOT (II) John Rinn BioFrontiers: www.colorado.edu/biofrontiers/john-rinn...

GGPLOT II : Going deeper into analysis and figure making (John Rinn Computational Genomics Lab)

20:08

GGPLOT II : Going deeper into analysis and figure making (John Rinn Computational Genomics Lab)

Просмотров 47Месяц назад

What is the difference between Pval and Padj? Let's explore this and other questions with our dox RNAseq time course. All while learning to make different types of figures in GGPLOT and interpret them. We will also refrain concepts in the previous class GGLPOT (I) . John Rinn Github: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/07_visualization_figures/02_plotting_ggplot_2.Rmd John ...

Making RNAseq FIgures ! (John Rinn Computational Genomics)

18:15

Making RNAseq FIgures ! (John Rinn Computational Genomics)

Просмотров 95Месяц назад

We are going to begin our journey of making figures using GGPLOT2. This is one of the most powerful figure making packages in R. We will do this in three parts - here is part 1 ! John Rinn Computational Genomics Lab: lncrna.io/teaching John Rinn BioFrontiers: www.colorado.edu/biofrontiers/john-rinn John Rinn Lab: lncRNA.io John Rinn Teaching: lncrna.io/teaching John Rinn University of Colorado ...

One script to run all the RNAseq Analyses (John Rinn Computational Genomics Lab)

6:38

One script to run all the RNAseq Analyses (John Rinn Computational Genomics Lab)

Просмотров 85Месяц назад

Here we will distill all the lesson in level 6 into one R markdown file - watch how fast all your hard work will pay off ! After this we will move to making figures! John Rinn BioFrontiers: www.colorado.edu/biofrontiers/john-rinn John Rinn Lab: lncRNA.io John Rinn Teaching: lncrna.io/teaching John Rinn University of Colorado Boulder Biochemistry: www.colorado.edu/biochemistry/john-rinn John Rin...

Let's analyze our RNAseq data in TPM (transcripts per million). John Rinn Computational Genomics Lab

30:50

Let's analyze our RNAseq data in TPM (transcripts per million). John Rinn Computational Genomics Lab

Просмотров 153Месяц назад

TPM Time ! Up until now we have been using counts data to analyze our data but now we will explore TPMs (Transcripts Per Million). This is a measure of "how much" of a given gene is expressed at each time point. It's typically used to measure how much a gene changes in abundance after dox exposure and the variance of that change. John Rinn Computational Genomics Lab Website: www.lncrna.io/cgl-l...

Let's now explore and analyze all our results! John Rinn Computational Genomics Lab

23:36

Let's now explore and analyze all our results! John Rinn Computational Genomics Lab

Просмотров 86Месяц назад

Here we are going to start the really fun analyses of filtering to which genes are significantly changing due to dox exposure in stem cells. Let's go find out new results ! John Rinn Teaching Website for this lesson: www.lncrna.io/cgl-level-6 John Rinn Github for this lesson: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/06_Differential_expression_analyses/04_exploring_results.Rmd #c...

Extract all DESEQ results using a for-loop. John Rinn Computational Genomics Lab (CGL)

14:11

Extract all DESEQ results using a for-loop. John Rinn Computational Genomics Lab (CGL)

Просмотров 45Месяц назад

Here we are going to learn for-loop logic to go into our DESEQ DDS object and extract all the results for each time comparison. This way we will have a data frame of all our results and can start to dig into deeper analysis. John Rinn Teaching Website for this class: www.lncrna.io/cgl-level-6 John Rinn Github for this class: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/06_Differenti...

Let's explore the DESEQ results files ! John Rinn Computational Genomics Lab.

16:38

Let's explore the DESEQ results files ! John Rinn Computational Genomics Lab.

Просмотров 75Месяц назад

Here we are going to go into our DDS object created from DESEQ and start to look at the results of 0 vs 12 hours dox exposure. We will learn how to find significant genes that are differentially expressed and much more - all while learning new R skills John Rinn Teaching Website for this class: www.lncrna.io/cgl-level-6 John Rinn Github for this class: github.com/boulderrinnlab/MASTER_CLASS/blo...

Time for DESEQ RNAseq Analysis! (John Rinn Computational Genomics Lab)

10:29

Time for DESEQ RNAseq Analysis! (John Rinn Computational Genomics Lab)

Просмотров 90Месяц назад

Today is the day we have all the materials we need to run DESEQ2 - let's go !! John Rinn Class Website: www.lncrna.io/teaching John Rinn Github: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/06_Differential_expression_analyses/01_run_DESEQ2.Rmd #Johnrinn #rnaseq #bioinformatics #rinn

Let's make our DESEQ Sample Sheet! John Rinn Computational Genomics Lab

10:39

Let's make our DESEQ Sample Sheet! John Rinn Computational Genomics Lab

Просмотров 57Месяц назад

Today we are going to be learning some more R skills to make a sample sheet as a required input to DESEQ2 to analyze our RNA sequencing data. After this step we are ready to level up and start our DESEQ2 analyses ! John Rinn Computational Genomics Lab (Lesson 05 / 04_sample_sheet). John Rinn Class website : www.lncrna.io/teaching John Rinn Github github.com/boulderrinnlab RMD for this class: gi...

Let's read in our RNAseq data into R ! John Rinn Computational Genomics Lab

17:00

Let's read in our RNAseq data into R ! John Rinn Computational Genomics Lab

Просмотров 137Месяц назад

We are now ready to start reading in our data ! Let's learn some basic R skills in R studio to get started. We will start to read in the results from the nextflow RNAseq pipeline and then get it all set for DESEQ analysis to find genes regulated by dox across time. We will also learn how to save our work in R. Let's get started! John Rinn Class website: www.lncrna.io/teaching John Rinn Github: ...

Package Delivery !! Let's start installing R packages !! John Rinn computational genomics lab.

11:33

Package Delivery !! Let's start installing R packages !! John Rinn computational genomics lab.

Просмотров 737 месяцев назад

We are now ready to explore over 20,000 FREE R packages in CRAN (Comprehensive R Archive Network) and Bioconductor. We will install a package from each repository that will apply to all 20,000 Freely available R packages. Each package will allow us to carry out complex functions and even how to code more cleanly (Tidyverse). From CRAN we will install tidyverse. From Bioconductor we will install...

CU Students: R Studio PRO on FIji. John Rinn Computational Genomics Lab

9:57

CU Students: R Studio PRO on FIji. John Rinn Computational Genomics Lab

Просмотров 837 месяцев назад

We will be using R studio PRO in class - it's an online version of R studio and has a few extra set up tasks. Let's walk through what you need to do. You have to have a CU identikey to use R studio PRO for in class coding. John Rinn Class Website: www.lncrna.io/cgl-level-5 Github instructions: github.com/boulderrinnlab/MASTER_CLASS/blob/main/lessons/05_R_data_R_studio/01_2_CU_STUDENTS_R_STUDIO_...