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12 materials found

Keywords: Experimental-design  or Flow cytometry data 


ChIP-seq analysis using R - Experimental design and peak calling.

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling-cfd4c18f-6c86-45ae-ab0b-630422c76af6 This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation
ChIP-seq analysis using R

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-5049bc9c-9bbb-4a6b-9244-37ed3980da0e ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming
ChIP-seq analysis using R - Experimental design and peak calling.

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation
ChIP-seq analysis using R - Quality Control

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
ChIP-seq analysis using R - File formats and QC

This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - File formats and QC https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-file-formats-and-qc This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
ChIP-seq analysis using R - Quality Control Walkthrough

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control Walkthrough https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control-walkthrough This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
Flow Cytometry 2013 Module 4 - 1D Static gating

How to create a constant gate for the whole data set for one channel by first creating a sample representative of the whole data set How to apply a static gate to all samples and count the proportions of cells lying on either side of the gate Visualizing the proportions using a density...

Keywords: 1d static gating, Flow cytometry data

Flow Cytometry 2013 Module 4 - 1D Static gating https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-4-1d-static-gating How to create a constant gate for the whole data set for one channel by first creating a sample representative of the whole data set How to apply a static gate to all samples and count the proportions of cells lying on either side of the gate Visualizing the proportions using a density plot, histogram, bean/violin plot Automating a sequential gating strategy in R to obtain cell proportions for a desired phenotype 1d static gating, Flow cytometry data 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 6 - Clustering and Additional FCM Tools

Lecture on FlowCAP (Flow Cytometry: Critical Assessment of Population Identification Methods) project K-means explained flowMeans: smart k-means for FCM data flowClust3.0, SPADE, flowBin, flowFP, SamSPECTRAL clustering Biomarker discovery: flowType and RchyOptimyx, advanced tools used...

Keywords: Biomarker discovery, Flow cytometry data, Flowcap

Flow Cytometry 2013 Module 6 - Clustering and Additional FCM Tools https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-6-clustering-and-additional-fcm-tools Lecture on FlowCAP (Flow Cytometry: Critical Assessment of Population Identification Methods) project K-means explained flowMeans: smart k-means for FCM data flowClust3.0, SPADE, flowBin, flowFP, SamSPECTRAL clustering Biomarker discovery: flowType and RchyOptimyx, advanced tools used to explore novel phenotypes and find ones which correlate with a clinical diagnosis More R: Bioconductor.org, an open source software project full of bioinformatics packages created for R, including sample work flows GenePattern.org: web-interface for running analysis modules such as sample deidentication, extracting specic keywords, quality control, normalization, clustering, classification FlowRepository.org: online FCM data repository to share public or private data sets with collaborators while providing detailed descriptions of the experiment set up and each FCS file Biomarker discovery, Flow cytometry data, Flowcap 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 5 - 1D Dynamic gating

Using quantiles to set a gate based on a negative control Using median and standard deviation to set a gate based on a negative control Exploring rangeGate: an automated way to set a 1D gate for each sample individually Recording proportions of cells in subpopulations of interest by...

Keywords: 1d dynamic gating, Flow cytometry data

Flow Cytometry 2013 Module 5 - 1D Dynamic gating https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-5-1d-dynamic-gating Using quantiles to set a gate based on a negative control Using median and standard deviation to set a gate based on a negative control Exploring rangeGate: an automated way to set a 1D gate for each sample individually Recording proportions of cells in subpopulations of interest by creating a spreadsheet file Recording a visual record of the gating results by creating JPEG image files 1d dynamic gating, Flow cytometry data 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 3 - Preprocessing and Quality Assurance of FCM Data

Preprocessing Removing margin events Data transformation: log vs. biexponential Data normalization Quality Assurance Overview of quality assurance concepts: total raw/viable cell count, margin event count, outlier detection based on density of common...

Keywords: Flow cytometry data, Preprocessing, Quality assurance

Flow Cytometry 2013 Module 3 - Preprocessing and Quality Assurance of FCM Data https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-3-preprocessing-and-quality-assurance-of-fcm-data Preprocessing Removing margin events Data transformation: log vs. biexponential Data normalization Quality Assurance Overview of quality assurance concepts: total raw/viable cell count, margin event count, outlier detection based on density of common parameters Building quality assurance objects using flowQ and generating summary HTML reports Flow cytometry data, Preprocessing, Quality assurance 2013-06-26 2017-10-09
ChIP-Seq

No description available

Keywords: ChIP-Seq, Experimental-design, QC, ChIP-Seq-QC, Data-format, Alignment, Peak-calling, Differential-binding, Annotation

ChIP-Seq https://tess.elixir-europe.org/materials/chip-seq No description available ChIP-Seq, Experimental-design, QC, ChIP-Seq-QC, Data-format, Alignment, Peak-calling, Differential-binding, Annotation
ChIP-seq analysis using R

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation