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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

MACS2 BDGCMP

 August 14, 2021

MACS2 bdgcmp for two bedgraph peak callingKeep it as 1.0 or default in most … bdgcmp Deduct noise by comparing two signal tracks in bedGraph.

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Tagged bdgcmp, BED, bedGraph, MACS

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Silvertuesday.com – AlphaFold 2 & Equivariance →
← BLASTN BAM FILE

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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
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Visualization and analysis of highly multiplexed imaging data - Nils Eling
Visualization Analysis IMC Data - March 28, 2022
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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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