rivm-bioinformatics Goto Github PK
Name: Infectieziekteonderzoek, Diagnostiek en laboratorium Surveillance-Bioinformatics (RIVM, The Netherlands)
Type: Organization
Location: Netherlands
Name: Infectieziekteonderzoek, Diagnostiek en laboratorium Surveillance-Bioinformatics (RIVM, The Netherlands)
Type: Organization
Location: Netherlands
AminoExtract is a tool for translating and extracting amino acid sequences from nucleotide-sequences based on a GFF input
A tool in order to accurately remove primer sequences from NGS reads in an amplicon experiment
Reference mapping workflow for the analysis of fungal samples
Apollo pipeline for the interpretation of variants identified through reference-based mapping
Quick estimation of Candida auris clade using mash
Conda recipes for the bioconda channel.
Re-formatting Fasta headers to fit CLC bio. Requested by the AMR group.
Creating and uploading containers to ghcr
Code for the website used for documenting bacteriology pipelines (tailor made for RIVM people). Written in R (bookdown)
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Annotation of chromosomes and plasmids of bacteria (AMR group)
Pipeline to process raw sequencing data up to de-novo assembly and the accompanying statistics
Automated BLASTing from fasta files.
Pipeline to perform cgMLST (or wgMLST) analysis. At the moment it just handles few genera for cgMLST
Package containing the basic classes that are used as base for the wrappers of the other Juno pipelines
Reference-based mapping Juno pipeline
Pipeline for serotyping Streptococcus pneumoniae (to be merged in Juno-typing).
Pipeline to perform SNP analysis in bacterial samples.
Pipeline to perform bacterial typing (7-locus MLST and serotyping when appropriate). It works with several (but not all) species/genera.
Pipeline to process raw sequencing data up to de-novo assembly and the accompanying statistics(iontorrent edition)
Pipeline to call minority variants in Mycobacterium samples
Internal R package (for RIVM) for making quality control reports of reference samples. Different assembly metrics are followed up and plotted over time.
SARS2seq is a pipeline designed to process raw FastQ data from targeted SARS-CoV-2 sequencing and generate biologically correct consensus sequences of the SARS-CoV-2 genome.
TrueConsense is a consensus caller for viral-targets that create biologically correct consensus sequences. TrueConsense keeps track of open reading frames, compensates for common sequencing or alignment artefacts, and is able to generate consensus sequences on multiple coverage-thresholds at the same time
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