Mehmet Tekman
Contributions
The following list includes only slides and tutorials where the individual has been added to the contributor list. This may not include the sum total of their contributions to the training materials (e.g. GTN css or design, tutorial datasets, workflow development, etc.) unless described by a news post.
GitHub Activity
Tutorials
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Single Cell
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Pre-processing of Single-Cell RNA Data
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Single Cell
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Downstream Single-cell RNA analysis with RaceID
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Single Cell
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Inferring Trajectories using Scanpy - Jupyter Notebook
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Single Cell
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Comparing inferred cell compositions using MuSiC deconvolution
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Single Cell
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Pre-processing of 10X Single-Cell RNA Datasets
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Single Cell
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Analysis of plant scRNA-Seq Data with Scanpy
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Single Cell
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Creating the bulk RNA-seq dataset for deconvolution
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Single Cell
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Bulk RNA Deconvolution with MuSiC
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Single Cell
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Creating the single-cell RNA-seq reference dataset for deconvolution
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Single Cell
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Understanding Barcodes
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Single Cell
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Clustering 3K PBMCs with Scanpy
Slides
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Single Cell
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Dealing with Cross-Contamination in Fixed Barcode Protocols
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Single Cell
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An introduction to scRNA-seq data analysis
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Single Cell
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Plates, Batches, and Barcodes
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Single Cell
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Clustering 3K PBMCs with Scanpy
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Single Cell
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Introducción al análisis de datos de scRNA-seq
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Single Cell
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Una introducción al análisis de datos scRNA-seq
News
29 November 2022
Authors: 
Mehmet Tekman
Wendi Bacon
The still new and shiny single-cell analysis topic now boasts a deconvolution tutorial suite! What does deconvolution do you ask? Well, in this context, it infers cell proportions from bulk RNA-seq data. You heard that correctly - instead of expensive new single-cell experiments, you can re-analyse old bulk RNA-seq data and estimate cell proportions. All you need is a reasonably good single cell dataset to use as a reference and you’re good to go! The tutorial suite shows you how to build your reference from publicly available single cell data, and apply analysis to some publicly available bulk RNA-seq data.
Full Story
18 November 2022
Authors: Wendi BaconMehmet Tekman
Single-cell analysis now has it’s own topic! These tutorials were previously part of the transcriptomics topic, but due to the amazing efforts byWendi Bacon,Mehmet Tekmanand others, we now have so many single-cell analysis tutorials that they deserve their own dedicated topic! From introductory slides and practicals, to case study tutorials generating cell clusters and trajectories from raw sequencing files, and even a growing subtopic of smaller tips and tricks for adapting analysis to user needs, the single cell topic either has what you need or is working on it. Come learn or get involved!
Full Story
30 March 2021
Authors: Mehmet Tekman
Beatriz Serrano-Solano
Single cell RNA-seq analysis is a cornerstone of developmental research and provides a great level of detail in understanding the underlying dynamic processes within tissues. In the context of plants, this highlights some of the key differentiation pathways that root cells undergo.
Full Story
Mehmet TekmanWendi Bacon
The still new and shiny single-cell analysis topic now boasts a deconvolution tutorial suite! What does deconvolution do you ask? Well, in this context, it infers cell proportions from bulk RNA-seq data. You heard that correctly - instead of expensive new single-cell experiments, you can re-analyse old bulk RNA-seq data and estimate cell proportions. All you need is a reasonably good single cell dataset to use as a reference and you’re good to go! The tutorial suite shows you how to build your reference from publicly available single cell data, and apply analysis to some publicly available bulk RNA-seq data.
Full Story
Wendi BaconMehmet Tekman
Single-cell analysis now has it’s own topic! These tutorials were previously part of the transcriptomics topic, but due to the amazing efforts byWendi Bacon,Mehmet Tekmanand others, we now have so many single-cell analysis tutorials that they deserve their own dedicated topic! From introductory slides and practicals, to case study tutorials generating cell clusters and trajectories from raw sequencing files, and even a growing subtopic of smaller tips and tricks for adapting analysis to user needs, the single cell topic either has what you need or is working on it. Come learn or get involved!
Full Story
Mehmet TekmanBeatriz Serrano-Solano
Single cell RNA-seq analysis is a cornerstone of developmental research and provides a great level of detail in understanding the underlying dynamic processes within tissues. In the context of plants, this highlights some of the key differentiation pathways that root cells undergo.
Full Story