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Open Source Biology & Genetics Interest Group

Open source tools and preprints for in vitro biology, genetics, bioinformatics, crispr, and other biotech applications.

 Posted in Research

3 Questions on… Picking the Right Tumor Cell Models for Research

 August 11, 2021

Technologies that have enabled this include tumoroids, and genome engineering techniques, such as CRISPR/Cas9. Patient-derived xenografts …

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Tagged cas9, crispr, xenografts

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Error when trying to import GTF files using rtracklayer’s import function →
← is local ancestry inference typically always run w/ array genotypes instead of imputed genotypes?

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Videos

European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany (talks only) https://eurobioc2022.bioconductor.org/schedule/ 09:00 Keynote Dr. Björn Grüning: Developing interoperable frameworks for the scientific community 09:45 Flashtalks 10:30 Coffee break 11:00 Special session Birds-of-a-Feather, Three parallel sessions 12:00 Lunch 13:00 Special session Birds-of-a-Feather, Three parallel sessions 14:30 Coffee break 14:50 End of Day 3 Closing remarks
EuroBioC2022 Live Stream Day 3: morning
European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany (talks only) https://eurobioc2022.bioconductor.org/schedule/ 16:20 Short talk Short talk 19: DifferentialRegulation: a novel approach to identify differentially regulated genes. Simone Tiberi 16:30 Short talk Short talk 20: Analysis of transposable elements in R and Bioconductor with atena. Beatriz Calvo-Serra 16:40 Short talk Short talk 21: Inclusive instruction in cancer data science: Authoring and deployment with yes4cure. Alexandru Mahmoud
EuroBioC2022 Live Stream Day 2: afternoon
European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany (talks only) https://eurobioc2022.bioconductor.org/schedule/ 14:35 Keynote Dr. Michael Dorrity: Developmental robustness of zebrafish embryos at single-cell resolution
EuroBioC2022 Live Stream Day 2: noon
European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany (talks only) https://eurobioc2022.bioconductor.org/schedule/ 09:15 Keynote Dr. Judith Zaugg 10:00 Coffee break 10:10 Short talk Short talk 8: Smooth epigenomics data analysis and visualisation with Bioconductor (or: an ode to Rle). Pierre-Luc Germain 10:20 Short talk Short talk 9: MethQuant: A package providing entropy-based measures for quantifying patterns of DNA methylation heterogeneity in (single-cell) bisulfite sequencing data. Emanuel Sonder 10:30 Short talk Short talk 10: DeeDee - Evaluating, Visualizing, and Integrating Results from Differential Expression Analysis Workflows. Federico Marini 10:40 Short talk Short talk 11: Analysing multiplexed assays of variant effects with mutscan. Michael Stadler 10:50 Short talk Short talk 12: Joint modeling of rare variant genetic effects using deep learning and data-driven burden scores. Brian Clarke 11:00 Coffee break 11:30 Short talk Short talk 13: spillR: Causal Modelling of Spillover in Mass Cytometry. Marco Guazzini 11:40 Short talk Short talk 14: Multi-omic integration with cosmosR and ocEAn to study cross-talks between signalling and metabolism in diseases. Aurelien Dugourd 11:50 Short talk Short talk 15: A new principled approach for single-cell proteomics data analysis. Laurent Gatto 12:00 Short talk Short talk 16: Analyzing hydrogen-deuterium exchange mass-spectrometry data in R. Oliver Crook 12:10 Short talk Short talk 17: CTexploreR, a package to explore CT genes. Axelle Loriot
EuroBioC2022 Live Stream Day 2: morning
European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany (talks only) https://eurobioc2022.bioconductor.org/schedule/ 14:10 Keynote Dr. Julio Saez-Rodriguez: Combining multi-omics data and biological knowledge to extract disease mechanisms
EuroBioC2022 Live Stream Day 1: afternoon
European Bioconductor Conference 2022 Live Stream from Heidelberg, Germany QUESTIONS: www.slido.com #1680070 (talks only) https://eurobioc2022.bioconductor.org/schedule/ 09:15 Introduction Welcome, Bioconductor overview, and Code of Conduct 09:40 Keynote Dr. Shila Ghazanfar: Integrative analyses for spatial genomics data 10:25 Break 10:30 Short talk Short talk 1: Co-clustering of Spatially Resolved Transcriptomic Data. Andrea Sottosanti 10:40 Short talk Short talk 2: Simplified, strand aware and comprehensive splicing analysis using IntEREst (1.22.0). Ali Oghabian 10:50 Short talk Short talk 3: Differential embedding analysis of multi-condition single-cell datasets. Constantin Ahlmann-Eltze 11:00 Coffee break 11:30 Short talk Short talk 4: Clinical microbiome data science with MultiAssayExperiment. Tuomas Borman 11:40 Short talk Short talk 5: µSTASIS - Assessment of human microbiota stability across longitudinal samples. Pedro Sánchez-Sánchez 11:50 Short talk Short talk 6: OmicSHIELD: privacy-protected federated omic data analysis in multi-center studies with Bioconductor through DataSHIELD. Juan Ramon Gonzalez 12:00 Short talk Short talk 7: DepInfeR - A Bioconductor package for Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling. Junyan Lu
EuroBioC2022 Live Stream Day 1: morning
Visualization and analysis of highly multiplexed imaging data - Nils Eling
Visualization Analysis IMC Data - March 28, 2022
Spatial Transcriptomics Technologies and Analysis Tools - Dario Righelli Analysing Spatially Resolved Transcriptomics Data with Bioconductor - Helena L. Crowell
Spatial Transcriptomics - January 31, 2022
Rにおけるバイオ画像解析入門: Introduction to Bioimaging Analysis in R 久米 慧嗣 Satoshi Kume (大阪電気通信大学 Osaka Electro-Communication University, 日本 Japan) 4:00 PM - 5:00 PM JST (Japan Standard Time) on Thursday, Nov. 4th, 2021 JAPANESE WORKSHOP このワークショップでは、BioconductorパッケージであるEBImageを使って、Rでの画像処理・画像解析の基本的な方法を扱う。次に、BioImageDbsパッケージを用いて、ExperimentHubからの画像データの取得を行う。さらに、rMiWパッケージが提供する、Deep learningモデルの１つであるU-NETモデルを用いて、教師有り画像セグメンテーション（領域分割）を学び。このワークショップは、Orchestra環境にて実施する。 This workshop covers basic methods of the image processing and image analysis in R using the Bioconductor package “EBImage” and the Orchestra platform. In addition, the image dataset is obtained from ExperimentHub using the “BioImageDbs” package. Using this dataset, we perform a supervised image segmentation using the U-NET model, one of deep learning models, provided by the rMiW package. Moderator: 露崎 弘毅 Koki Tsuyuzaki (理化学研究所 RIKEN, 日本 Japan)
Rにおけるバイオ画像解析入門: Introduction to Bioimaging Analysis in R
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