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Biostatsquid
Spain
เข้าร่วมเมื่อ 3 พ.ย. 2022
Welcome to Biostatsquid!
In this channel, you will find clear explanations and hands-on tutorials for analysing and interpreting biological data.
- Learn basic techniques in biostatistics, from heatmaps to pathway enrichment analysis.
- Manage your data and create publication-ready visualisations by following my easy step-by-step tutorials in R and Python.
- Practical explanations without complex formulas for you to understand your datasets and be able to interpret your results.
Are you ready to dive in? Don't miss any other video and hit that subscribe button!
In this channel, you will find clear explanations and hands-on tutorials for analysing and interpreting biological data.
- Learn basic techniques in biostatistics, from heatmaps to pathway enrichment analysis.
- Manage your data and create publication-ready visualisations by following my easy step-by-step tutorials in R and Python.
- Practical explanations without complex formulas for you to understand your datasets and be able to interpret your results.
Are you ready to dive in? Don't miss any other video and hit that subscribe button!
Detect and remove doublets in R (scRNAseq)
In this tutorial I will explain how to remove doublets from scRNAseq data in R using R package after running one or more doublet detection tools. For this tutorial, I’ll be using RStudio, and you’ll need the tidyverse packages as well as Seurat.
You will learn how to:
- get doublet/singlet count and percentage for one or more doublet detection tools
-get doublet vs singlets stats
-remove high-confidence doublets from your Seurat object
- and more!
And as always, you can find the code I am using in this tutorial at biostatsquid.com, where you can also find a step by step explanation of the code. For this tutorial you will need R, or Rstudio, and you will need to install the package listed above.
Hope you like it!
--------------------------------------------------------------------------------------------------------------------
Watched it already?
If you liked this video or found it useful, please let me know! Your comments and feedback are very much appreciated😊
If you have questions, don't hesitate to leave me a comment down below, I will answer as soon as I can:)
If you like my content and would like to support me (in a more capitalistic manner), you might consider buying me a coffee.
www.buymeacoffee.com/biostatsquid
Big thanks for your support!
--------------------------------------------------------------------------------------------------------------------
Are you into biostatistics and computational analysis?
For more biostatistics tools and resources, you can visit:
biostatsquid.com/
Follow me on Instagram at @biostatsquid for more
• simple and clear explanations of biostatistics methods
• computational biology tools
• easy step-by-step tutorials in R and Python
to analyse and visualise your biological data!
Don’t forget to subscribe if you don’t want to miss another video from me!
You will learn how to:
- get doublet/singlet count and percentage for one or more doublet detection tools
-get doublet vs singlets stats
-remove high-confidence doublets from your Seurat object
- and more!
And as always, you can find the code I am using in this tutorial at biostatsquid.com, where you can also find a step by step explanation of the code. For this tutorial you will need R, or Rstudio, and you will need to install the package listed above.
Hope you like it!
--------------------------------------------------------------------------------------------------------------------
Watched it already?
If you liked this video or found it useful, please let me know! Your comments and feedback are very much appreciated😊
If you have questions, don't hesitate to leave me a comment down below, I will answer as soon as I can:)
If you like my content and would like to support me (in a more capitalistic manner), you might consider buying me a coffee.
www.buymeacoffee.com/biostatsquid
Big thanks for your support!
--------------------------------------------------------------------------------------------------------------------
Are you into biostatistics and computational analysis?
For more biostatistics tools and resources, you can visit:
biostatsquid.com/
Follow me on Instagram at @biostatsquid for more
• simple and clear explanations of biostatistics methods
• computational biology tools
• easy step-by-step tutorials in R and Python
to analyse and visualise your biological data!
Don’t forget to subscribe if you don’t want to miss another video from me!
มุมมอง: 277
วีดีโอ
Easy DoubletFinder tutorial in R (scRNAseq)
มุมมอง 3763 หลายเดือนก่อน
In this tutorial I will explain how to detect and remove doublets from scRNAseq data in R using R package DoubletFinder. For this tutorial, I’ll be using RStudio, and you’ll need the package DoubletFinder. You will learn how to: - run DoubletFinder -get doublet vs singlets stats -add doublet/singlet annotations to your Seurat object - and more! And as always, you can find the code I am using in...
Easy doublet detection in R with scDoubletFinder (scRNAseq)
มุมมอง 2913 หลายเดือนก่อน
In this tutorial I will explain how to detect and remove doublets from scRNAseq data in R using R package scDoubletFinder(). For this tutorial, I’ll be using RStudio, and you’ll need the package scDoubletFinder. You will learn how to: - run scDoubletFinder -get doublet vs singlets stats -add doublet/singlet annotations to your Seurat object - and more! And as always, you can find the code I am ...
How does doublet finder work? Easy explanation!
มุมมอง 3324 หลายเดือนก่อน
In this video, we will discuss the main concepts behind DoubletFinder, a doublet-finding tool for scRNAseq in R - easily explained! We will go through the main steps it uses to mark cells in your Seurat dataset as doublets. R tutorial coming up next! And as always, you can find the full explanation at biostatsquid.com: biostatsquid.com/ Hope you like it!
Violin plots tutorial with ggplot2 in R (part 2)
มุมมอง 2755 หลายเดือนก่อน
In this tutorial I will explain how to create and customise your own violin plots in R. In particular, we will cover facet_wrap, facet_grid, and how to create your own violin plot function. For this tutorial, I’ll be using RStudio, and you’ll need the package ggplot2. You will learn how to: - plot a violin plot in R - customise and edit labels, colours, themes - plot grouped violin plots - and ...
Violin plots tutorial with ggplot2 in R (part 1)
มุมมอง 1K5 หลายเดือนก่อน
In this tutorial I will explain how to create and customise your own violin plots in R. For this tutorial, I’ll be using RStudio, and you’ll need the package ggplot2. You will learn how to: - plot a violin plot in R - customise and edit labels, colours, themes - plot grouped violin plots - and more! And as always, you can find the code I am using in this tutorial at biostatsquid.com, where you ...
EASY violin plots and boxplots - simple explanation with examples
มุมมอง 7626 หลายเดือนก่อน
In this video, we will discuss the main concepts behind violin plots and boxplots - easily explained! We will go through what are violin plots and boxplots and how to interpret it and use it to visualise our biological data. And as always, you can find the full explanation at biostatsquid.com: biostatsquid.com/interpret-density-plots/ Hope you like it! Watched it already? If you liked this vide...
How to interpret density plots - simple explanation with examples!
มุมมอง 2.4K7 หลายเดือนก่อน
In this video, we will discuss the main concepts behind density plots - easily explained! We will go through what is a density plot and how to interpret it and use it to visualise our biological data. And as always, you can find the full explanation at biostatsquid.com: biostatsquid.com/interpret-density-plots/ Hope you like it! Watched it already? If you liked this video or found it useful, pl...
Logistic regression - easily explained with an example!
มุมมอง 1.7K7 หลายเดือนก่อน
In this video, we will discuss the main concepts behind Logistic regression - easily explained! We will go through what is logistic regression, when to use it and how to interpret the coefficients. And as always, you can find the full explanation at biostatsquid.com Hope you like it! biostatsquid.com/easy-logistic-regression/ Watched it already? If you liked this video or found it useful, pleas...
SingleR EASY TUTORIAL: step-by-step cell type annotation in R
มุมมอง 1.7K8 หลายเดือนก่อน
In this tutorial I will explain how to do cell type annotation with the R package SingleR. After a brief introduction to reference-based automatic cell type annotation and SingleR, we will go step by step through the workflow, including preparing our input data, running SingleR, interpreting the results and some tips and tricks to get the most out of SingleR. For this tutorial, I’ll be using RS...
COMPLETE SURVIVAL ANALYSIS tutorial in R: Kaplan-Meier, Cox regression, Forest Plots...
มุมมอง 8K11 หลายเดือนก่อน
In this tutorial, I will explain how to perform survival analysis in R, including log rank test, Cox regression, Kaplan-Meier curves, and more! We will use the R packages ggsurvplot, survminer and survival. You will learn how to: - plot a Kaplan Meier curve - test for differences between groups using the log rank test - build a survival model with Cox regression - and visualise your results wit...
COX REGRESSION and HAZARD RATIOS - easily explained with an example!
มุมมอง 23Kปีที่แล้ว
In this video, we will discuss the main concepts behind Cox regression for survival time analysis - easily explained! We will go through hazard ratios, coefficients, p-values and confidence intervals. I will also give you simple and practical guidelines on how to interpret the results from Cox regression, with an example! And as always, you can find the full explanation at biostatsquid.com Hope...
LOG RANK TEST for survival analysis - easily explained with an example!
มุมมอง 9Kปีที่แล้ว
In this video, we will discuss the main concepts behind the Log Rank Test - easily explained! I will also give you simple and practical guidelines on how to interpret the results from the Log Rank test And as always, you can find the full explanation at biostatsquid.com Hope you like it! biostatsquid.com/easy-log-rank-test/ Watched it already? If you liked this video or found it useful, please ...
How to interpret KAPLAN-MEIER curves - Easily explained!
มุมมอง 18Kปีที่แล้ว
In this video, we will discuss the main concepts behind Kaplan-Meier curves- easily explained! I will also give you simple and practical guidelines on how to interpret a Kaplan-Meier curve. And as always, you can find the full explanation at biostatsquid.com Hope you like it! biostatsquid.com/kaplan-meier-curve/ Watched it already? If you liked this video or found it useful, please let me know!...
Easy survival analysis - simple introduction with an example!
มุมมอง 3.6Kปีที่แล้ว
In this video, we will discuss the main concepts behind survival time analysis - easily explained! Survival time analysis is really common in biostatistics. You might have heard of Kaplan-Meier curves, Cox regressions or the log rank test. In clinical trials, survival time analysis is used to compare the performance of two different kinds of treatment, for example. Survival time analysis can al...
Top tips to create pretty plots in R (ggplot2)
มุมมอง 1.6Kปีที่แล้ว
Top tips to create pretty plots in R (ggplot2)
Gene Set Enrichment Analysis (GSEA) with fgsea - easy R tutorial
มุมมอง 11Kปีที่แล้ว
Gene Set Enrichment Analysis (GSEA) with fgsea - easy R tutorial
Pathway Enrichment Analysis plots: easy R tutorial
มุมมอง 10Kปีที่แล้ว
Pathway Enrichment Analysis plots: easy R tutorial
Pathway enrichment analysis tutorial in R with clusterProfiler()
มุมมอง 16Kปีที่แล้ว
Pathway enrichment analysis tutorial in R with clusterProfiler()
Step-by-step heatmap tutorial in R with pheatmap()
มุมมอง 12Kปีที่แล้ว
Step-by-step heatmap tutorial in R with pheatmap()
How to interpret a heatmap for differential gene expression analysis - simply explained!
มุมมอง 23Kปีที่แล้ว
How to interpret a heatmap for differential gene expression analysis - simply explained!
Mapping and aligning sequencing reads | NGS read preprocessing in R (Part 3)
มุมมอง 690ปีที่แล้ว
Mapping and aligning sequencing reads | NGS read preprocessing in R (Part 3)
Quality check on sequencing reads | NGS read preprocessing in R (Part 2)
มุมมอง 852ปีที่แล้ว
Quality check on sequencing reads | NGS read preprocessing in R (Part 2)
Quality check on sequencing reads | NGS read preprocessing in R (Part 1)
มุมมอง 3.7Kปีที่แล้ว
Quality check on sequencing reads | NGS read preprocessing in R (Part 1)
Standard scRNAseq preprocessing workflow with Seurat | Beginner R
มุมมอง 8Kปีที่แล้ว
Standard scRNAseq preprocessing workflow with Seurat | Beginner R
How to interpret GSEA results and plot - simple explanation of ES, NES, leading edge and more!
มุมมอง 29Kปีที่แล้ว
How to interpret GSEA results and plot - simple explanation of ES, NES, leading edge and more!
Gene Set Enrichment Analysis (GSEA) - simply explained!
มุมมอง 33Kปีที่แล้ว
Gene Set Enrichment Analysis (GSEA) - simply explained!
Pathway enrichment analysis - simple explanation!
มุมมอง 27K2 ปีที่แล้ว
Pathway enrichment analysis - simple explanation!
FDR, q-values vs p-values: multiple testing simply explained!
มุมมอง 12K2 ปีที่แล้ว
FDR, q-values vs p-values: multiple testing simply explained!
Correlation vs causation | Simple explanation with examples
มุมมอง 3.9K2 ปีที่แล้ว
Correlation vs causation | Simple explanation with examples
hi thank you for a very good video, how would you interpret the HR 7,4 for smoking in one of the slides? 7,4 times higher risc of death compared to non smokers?
Thank you so much for this video but we would like to see the codes you're running so that we can replicate the same
what is the career opportunities in this field
That's a german accent right? Many thanks for the video.. really enjoyed the explanations!
Thanks for the video, this really explains it in a nutshell! This may be not in your alley, but what would PC2 to be if you would plot geochemical data with each variable being an element (PC1 seems to be rock type). Thanks in advance!
Awesome! Thank you for sharing these insights. That's very helpful for my current research project and I decided to switch from SPSS to R ;-)
SUPERB THANKS <3
Perfect explanation for Principal Component Analysis
Thanks for your valuable tutorial.🙏🌹
First and foremost, thank you for providing such a detailed video. I am having an unusual difficulty with my data. I have 2345 significantly differentially expressed genes, and when I try to plot all of the significant genes, I can see all of the gene names on the volcano plot. However, when I try to visualize merely 30 or 100 genes, the codes work correctly but I am unable to see them. Could you help provide me some advice on how to solve this issue? Thank you in advance.
fix your mic
❤
Thanks
Thanks a lot
How do someone find out the linear combination of PC1?
So simple and clear. U are awesome.
This is the best tutorial I have ever seen. Thank you so much.
greatttttttttt. please keep on creating videos
I'm currently struggling a lot with biostats this video was very useful
Great video. It explained PCA in a very simple and clear way. Thank you!
i have suffered with PCA for two years and this video just made it so easy for me
thank u
thank u very much
Wonderful video, thank you very much!
Like your videos!
excellent !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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