Канал: NBISweden

SciLifeLab Big Talk: Animesh Acharjee

SciLifeLab Big Talk: Animesh Acharjee

NGS-Intro 6: Quality Control of NGS Data

NGS-Intro 6: Quality Control of NGS Data

NGS-Intro 5: Advanced Linux

NGS-Intro 5: Advanced Linux

NGS-Intro 2: Introduction to Uppmax

NGS-Intro 2: Introduction to Uppmax

NGS-Intro 1: Introduction to Linux

NGS-Intro 1: Introduction to Linux

NGS-Intro 9: Whole Genome Sequencing & Variant Calling Workflow

NGS-Intro 9: Whole Genome Sequencing & Variant Calling Workflow

NGS-Intro 11: Bulk RNA-Seq and Differential Gene Expression Workflow

NGS-Intro 11: Bulk RNA-Seq and Differential Gene Expression Workflow

NGS-Intro 12: Research Data Management

NGS-Intro 12: Research Data Management

NGS-Intro 4: Quality of Life | Better Terminal Experience

NGS-Intro 4: Quality of Life | Better Terminal Experience

NGS-Intro 3: Filetype in Bioinformatics

NGS-Intro 3: Filetype in Bioinformatics

NGS-Intro 13: NBIS Information & Services

NGS-Intro 13: NBIS Information & Services

NGS-Intro 7: NGS Technology & Challenges

NGS-Intro 7: NGS Technology & Challenges

NGS-Intro 8: NGS and Bioinformatic Pipelines

NGS-Intro 8: NGS and Bioinformatic Pipelines

NGS-Intro 10: Variant Calling Workflow | GATK Best Practices

NGS-Intro 10: Variant Calling Workflow | GATK Best Practices

09 Celltype deconvolution overview

09 Celltype deconvolution overview

02 Spatial Omics Overview

02 Spatial Omics Overview

11 Common Coordinated Framework

11 Common Coordinated Framework

03 Introduction to Image informatics

03 Introduction to Image informatics

04 Image pre processing

04 Image pre processing

05 Segmentation free cell identification

05 Segmentation free cell identification

06 Basic QC and data analysis with Scanpy

06 Basic QC and data analysis with Scanpy

07 ISS data analysis

07 ISS data analysis

10 Cell cell communication inference

10 Cell cell communication inference

08 Spatial Transcriptomics analysis with Squidpy

08 Spatial Transcriptomics analysis with Squidpy

01 Welcome and course introduction

01 Welcome and course introduction

09 Differential Gene Expression (part 1)

09 Differential Gene Expression (part 1)

02 RNAseq QC

02 RNAseq QC

12 Online Repositories

12 Online Repositories

06 Preprocessing

06 Preprocessing

10 Differential gene expression (part 2)

10 Differential gene expression (part 2)

05 Pseudoaligners

05 Pseudoaligners

08 Clustering

08 Clustering

13 Reading Bioinformatics

13 Reading Bioinformatics

11 Gene Set Analysis

11 Gene Set Analysis

03 Mapping

03 Mapping

01 Introduction to RNA biology

01 Introduction to RNA biology

07 Principal Component Analysis (PCA)

07 Principal Component Analysis (PCA)

04 Quantification

04 Quantification

2 Feature Selection

2 Feature Selection

08 PCA — 04 Summary

08 PCA — 04 Summary

FAIR principles in life science research practice - End of session, Niclas Jareborg

FAIR principles in life science research practice - End of session, Niclas Jareborg

FAIR principles in life science research practice - Keynote: First FAIR steps, Rob Hooft

FAIR principles in life science research practice - Keynote: First FAIR steps, Rob Hooft

FAIR principles in life science research practice - COVseq: making it FAIR, Luuk Harbers

FAIR principles in life science research practice - COVseq: making it FAIR, Luuk Harbers

FAIR principles in life science research practice - Automated cell profiling and AI, Ola Spjuth

FAIR principles in life science research practice - Automated cell profiling and AI, Ola Spjuth

FAIR principles in life science research practice - CRUSH Covid, Georgios Varotsis

FAIR principles in life science research practice - CRUSH Covid, Georgios Varotsis

FAIR principles in life science research practice - COVID-19 Data Portal, Arnold Kochari

FAIR principles in life science research practice - COVID-19 Data Portal, Arnold Kochari

FAIR principles in life science research practice - Keynote: FAIR Principles, Erik Schultes

FAIR principles in life science research practice - Keynote: FAIR Principles, Erik Schultes

FAIR principles in life science research practice - Introduction, Niclas Jareborg

FAIR principles in life science research practice - Introduction, Niclas Jareborg

01 Single Cell Technologies — 01 The Eukaryotic Single Cell Genomics Facility

01 Single Cell Technologies — 01 The Eukaryotic Single Cell Genomics Facility

01 Single Cell Technologies — 04 VDJseq

01 Single Cell Technologies — 04 VDJseq

01 Single Cell Technologies — 02 scRNAseq overview

01 Single Cell Technologies — 02 scRNAseq overview

01 Single Cell Technologies — 05 CITEseq

01 Single Cell Technologies — 05 CITEseq

01 Single Cell Technologies — 03 SMARTseq

01 Single Cell Technologies — 03 SMARTseq

01 Single Cell Technologies — 07 scATACseq

01 Single Cell Technologies — 07 scATACseq

01 Single Cell Technologies — 06 Cell Hashing and Multiplexing

01 Single Cell Technologies — 06 Cell Hashing and Multiplexing

01 Single Cell Technologies — 08 Conclusion

01 Single Cell Technologies — 08 Conclusion

03 Normalisation — 05 Scaling and Regressing Confounders

03 Normalisation — 05 Scaling and Regressing Confounders

03 Normalisation — 03 Cell Cycle Scoring

03 Normalisation — 03 Cell Cycle Scoring

03 Normalisation — 06 Conclusions

03 Normalisation — 06 Conclusions

03 Normalisation — 01 Normalisation Methods

03 Normalisation — 01 Normalisation Methods

03 Normalisation — 02 Imputation

03 Normalisation — 02 Imputation

03 Normalisation — 04 Feature Selection

03 Normalisation — 04 Feature Selection

02 Quality Control — 01 Introduction

02 Quality Control — 01 Introduction

02 Quality Control — 02 Transcription Bursting

02 Quality Control — 02 Transcription Bursting

07 Differential Expression — 06 Summary

07 Differential Expression — 06 Summary

07 Differential Expression — 04 Result Assessment

07 Differential Expression — 04 Result Assessment

07 Differential Expression — 03 Zero-inflated Models

07 Differential Expression — 03 Zero-inflated Models

07 Differential Expression — 05 Method Comparison

07 Differential Expression — 05 Method Comparison

07 Differential Expression — 01 Introduction

07 Differential Expression — 01 Introduction

06 Clustering — 08 Conclusion

06 Clustering — 08 Conclusion

06 Clustering — 04 Graphs

06 Clustering — 04 Graphs

06 Clustering — 06 HDBSCAN

06 Clustering — 06 HDBSCAN

06 Clustering — 05 Graph Partitioning

06 Clustering — 05 Graph Partitioning

06 Clustering — 03 K-means

06 Clustering — 03 K-means

06 Clustering — 02 Hierarchical Clustering

06 Clustering — 02 Hierarchical Clustering

06 Clustering — 07 Pagoda

06 Clustering — 07 Pagoda

05 Data Integration — 05 Summary

05 Data Integration — 05 Summary

06 Clustering — 01 Introduction

06 Clustering — 01 Introduction

05 Data Integration — 03 Graph-based Integration

05 Data Integration — 03 Graph-based Integration

05 Data Integration — 04 Integration Assessment

05 Data Integration — 04 Integration Assessment

05 Data Integration — 02 Linear Integration

05 Data Integration — 02 Linear Integration

05 Data Integration — 01 Introduction

05 Data Integration — 01 Introduction

04 Dimensionality Reduction — 06 Conclusion

04 Dimensionality Reduction — 06 Conclusion

04 Dimensionality Reduction — 05 UMAP

04 Dimensionality Reduction — 05 UMAP

04 Dimensionality Reduction — 02 PCA

04 Dimensionality Reduction — 02 PCA

04 Dimensionality Reduction — 04 tSNE

04 Dimensionality Reduction — 04 tSNE

04 Dimensionality Reduction — 01 Introduction

04 Dimensionality Reduction — 01 Introduction

04 Dimensionality Reduction — 03 Graphs

04 Dimensionality Reduction — 03 Graphs

02 Quality Control — 08 Conclusion

02 Quality Control — 08 Conclusion

02 Quality Control — 07 Filtering

02 Quality Control — 07 Filtering

02 Quality Control — 06 Doublets

02 Quality Control — 06 Doublets

02 Quality Control — 05 Spike-in RNAs

02 Quality Control — 05 Spike-in RNAs

02 Quality Control — 04 Sequencing Artefacts

02 Quality Control — 04 Sequencing Artefacts

02 Quality Control — 03 Single Cell Pre-processing

02 Quality Control — 03 Single Cell Pre-processing

10 Trajectory Inference — 07 Trajectory Differential Expression

10 Trajectory Inference — 07 Trajectory Differential Expression

11 Spatial Transcriptomics — 07 Summary

11 Spatial Transcriptomics — 07 Summary

09 Cell Type Prediction — 08 Summary

09 Cell Type Prediction — 08 Summary

09 Cell Type Prediction — 04 SVM Classifier

09 Cell Type Prediction — 04 SVM Classifier

10 Trajectory Inference — 02 ICA

10 Trajectory Inference — 02 ICA

09 Cell Type Prediction — 03 KNN Classifier

09 Cell Type Prediction — 03 KNN Classifier

11 Spatial Transcriptomics — 05 Spatially Aware Analysis

11 Spatial Transcriptomics — 05 Spatially Aware Analysis

10 Trajectory Inference — 06 RNA velocity

10 Trajectory Inference — 06 RNA velocity

10 Trajectory Inference — 01 Introduction

10 Trajectory Inference — 01 Introduction

08 Gene Set Analysis — 01 Introduction

08 Gene Set Analysis — 01 Introduction

08 Gene Set Analysis — 05 Summary

08 Gene Set Analysis — 05 Summary

09 Cell Type Prediction — 02 Classifiers Principles

09 Cell Type Prediction — 02 Classifiers Principles

10 Trajectory Inference — 04 Minimun Spanning Tree

10 Trajectory Inference — 04 Minimun Spanning Tree

07 Differential Expression — 02 Common Methods

07 Differential Expression — 02 Common Methods

11 Spatial Transcriptomics — 02 Spatial Technologies

11 Spatial Transcriptomics — 02 Spatial Technologies

09 Cell Type Prediction — 01 Introduction

09 Cell Type Prediction — 01 Introduction

10 Trajectory Inference — 05 Graph Abstraction

10 Trajectory Inference — 05 Graph Abstraction

08 Gene Set Analysis — 03 Overrepresentation Analysis

08 Gene Set Analysis — 03 Overrepresentation Analysis

11 Spatial Transcriptomics — 01 Introduction

11 Spatial Transcriptomics — 01 Introduction

09 Cell Type Prediction — 06 Method Comparison

09 Cell Type Prediction — 06 Method Comparison

09 Cell Type Prediction — 05 Methods Overview

09 Cell Type Prediction — 05 Methods Overview

11 Spatial Transcriptomics — 06 10X Visium

11 Spatial Transcriptomics — 06 10X Visium

10 Trajectory Inference — 08 Summary

10 Trajectory Inference — 08 Summary

08 Gene Set Analysis — 04 GSEA

08 Gene Set Analysis — 04 GSEA

11 Spatial Transcriptomics — 03 Analysis of Spatial Data

11 Spatial Transcriptomics — 03 Analysis of Spatial Data

08 Gene Set Analysis — 02 Gene Sets

08 Gene Set Analysis — 02 Gene Sets

10 Trajectory Inference — 03 Diffusion Maps

10 Trajectory Inference — 03 Diffusion Maps

09 Cell Type Prediction — 07 Hierarchical Progressive Learning

09 Cell Type Prediction — 07 Hierarchical Progressive Learning

11 Spatial Transcriptomics — 04 Spot Deconvolution

11 Spatial Transcriptomics — 04 Spot Deconvolution

SciLifeLab Big Talk : Molly Hammell

SciLifeLab Big Talk : Molly Hammell