Discover @lgatto Open Source projects

Laurent Gatto (@lgatto)

lgatto

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Registered over 13 years ago
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R
55.0 %

HTML
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Makefile 6.3 %

Python
2.5 %

Jupyter Notebook
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Dockerfile
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Location 🇧🇪 Belgium
Country Total Rank 201
Country Ranking

R
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HTML
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C++
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Jupyter Notebook
376

C#
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Python
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TeachingMaterial

Various teaching material

MSnbase

Base Classes and Functions for Mass Spectrometry and Proteomics

RforProteomics

Using R and Bioconductor packages for the analysis and comprehension of proteomics data.

rbc

tidies

A Grammar of Data Manipulation for Omics Data

2016-02-25-adv-programming-EMBL

More robust R programming, testing and debugging

pRoloc

A unifying bioinformatics framework for organelle proteomics

advr1

Advanced R 1-day course taught at the University of Cambridge

2017-04-03-adv-r-progr-EMBL

Advanced R programming course at EMBL, 3-4 April 2017

rols

An R package to query EBI's Ontology Lookup Service (OLS)

spr

Scientific Programming with R

R-programming

Writing better R code

Pbase

Manipluating and exploring protein and proteomics data

SC-ICS-Proposal

Software Carpentry ICS proposal

rccpp

Using C and C++ code from R

tipsntRicks

A collection R tips and tRicks

lgatto.github.io

pRolocGUI

Interactive visualisation and exploration of spatial proteomics data

Quantitative-Proteomics-and-Data-Analysis

Material Quantitative Proteomics and Data Analysis Course

S4-tutorial

An tutorial on R S4 object oriented programming

roo

R object oriented programming

hpar

A simple interface to the Human Protein Atlas

slide-templates

A set of templates for presentations

sequences

Educational package used in an R course to illustrate OO programming and package development.

pRolocdata

Data accompanying the pRoloc package

proteowizard

The ProteoWizard Library and Tools for - http://proteowizard.sourceforge.net/

synapter

Label-free data analysis pipeline for optimal identification and quantitation

2017_11_09_Rcourse_Jena

R course, Leibniz Fritz Lipmann Institute, Jena

2015-03-05-Intro-Integ-Omics-Prot

Introduction to Integrative Omics

ms-coding-standards

Guidelines for publication of code related to mass spectrometry data analysis

QFeaturesScpWorkshop2021

QFeatures and scp Bioc2021 workshop

rosio

rosio: An R interface to OpenSensors.io

R-functional-programming

Short lecture about functional programming in R

ProteomicsBioc2016Workshop

R/Bioconductor tools for mass spectrometry-based proteomics

2016-10-rbioc-prot-Stellenbosch

Material for R/Bioconductor Proteomics Workshop at Stellenbosch University, October 2016

qcmetrics

An R framework for quality control

2017-05-03-RstatsIntro-NEU

Beginner's statistics in R

2018_07_09_CSAMA_Brixen

An introduction to mass spectrometry-based proteomics

sticker

Create hex sticker in R

rpx

R Interface to the ProteomeXchange Repository

Spectrum

Spectrum Infrastructure for Mass Spectrometry Data

ProteomicsAnnotationHubData

Annotation hub data for proteomics data

msGUI

Mass spectrometry data browser

r-bioc-ms-challenges

Current and future challenges for MS-based omics

QuickPackage

A 5 minute introduction on writing R packages

RPackageDevelopment

R package develeopment

bioc-ms-prot

Material about R/Bioconductor for mass spectrometry and proteomics

2018-TAGM-paper

2018 TAGM paper

2021_05_13_MayInstitute

Material for my May Institute 2021 keynote talk

rr-rmarkdown-intro-slides

Rmarkdown for reproducible research slides

biocpkgs

Retrieve Bioconductor package download data

2020-msnbase-v2

MSnbase v2 paper

Bioc2013-poster

'Using R and Bioconductor for proteomics data analysis' poster for the Bioconductor 2013 conference

QSep-manuscript

Assessing sub-cellular resolution in spatial proteomics experiments

open-scholarship-curriculum

An open scholarship curriculum

R-debugging

2021_08_31_RProtAZ_online

Exploring, visualising and analysing mass spectrometry-based proteomics data in R

R-parallel

Short lecture about parallelisation in R

2016-11-17-cam

Introduction to working with data for Humanities Researchers

Jupyter Notebook

RBasics

A general introduction to R for bioinformaticians familiar with programming/scripting

open-rr-bioinfo-best-practice

Best practices in bioinformatics research: open source software and reproducibility

Jupyter Notebook

rbioc-proteomics

Using R/Bioc for proteomics

physalia2023

Physalia 2023 course notes

2017-03-30-OSC-peerreview

Slides for my talk at the How to Get the Most Out of Modern Peer Review workshop

R-vectorisation

Short lecture about vectorisation in R

VisualisingBiomolecularData

Visualising biomolecular data

BiocMassSpecWorkingGroup

Bioconductor Mass Spectrometry Working Group

2019_05_16_rr_Delft

My talk at the 'Are you ready for publishing reproducible research?' meeting

physalia2022

Physalia 2022 notes

ProteomicsBioc2014Workshop

Bioc2014 workshop on R / Bioconductor packages for Proteomics

statistics-primer

Statistics primer

2015-05-14-Stellenbosch

Software Carpentry Bootcamp, Stellenbosch, South Africa

bioc-pRolocGUI-workflow

pRolocGUI F1000research workflow

interactive-vis-intro

hort introduction to interactive visualisation in R

QFeaturesWorkshop2020

QFeatures: Quantitative features for mass spectrometry data

UniProt.REST

R Interface to UniProt REST API

2017_11_16_OpenConCam

OpenConCam 2017: The #BulliedIntoBadScience campaign

2016-05-16-CAM

Data Carpentry, University of Cambridge, 16-17 May 2016

marts

Listing of mart instances

R-bmark-prof-optim

R benchmarking, profiling and optimisation

2017-spatialmap-robin

Robin's 'Spatial Proteomics Data Dissemination' project

workbench-bioc-intro

Introduction to genomic data analysis with R and Bioconductor

MLInterfaces

Uniform interfaces to R machine learning procedures for data in Bioconductor containers - see http://bioconductor.org/packages/release/bioc/html/MLInterfaces.html for official code.

2014_10_HUPO_Madrid

Material for HUPO 2014 in Madrid

2015-09-10-CAM

ElixirUK: Data Carpentry

RpepXML

RpepXML is an R package that allows to import and manipulate pepXML files -- see Wiki for more details.

RIntro

An introduction to R for beginners, using microarrays as main thread