-
Bejo Zaden
- Leiden
-
22:42
(UTC +01:00) - www.jboom.org
- https://orcid.org/0000-0001-5845-5364
- https://nl.linkedin.com/in/jasperboom
Stars
dnscrypt-proxy 2 - A flexible DNS proxy, with support for encrypted DNS protocols.
Interactive Data Visualization in the browser, from Python
Data validation using Python type hints
Plugins for the Ensembl Variant Effect Predictor (VEP)
NEAT (NExt-generation Analysis Toolkit) simulates next-gen sequencing reads and can learn simulation parameters from real data.
Configure workflow/pipeline tests using yaml files.
A BioWDL variantcalling pipeline for germline DNA data. Starting with FASTQ files to produce VCF files. Category:Multi-Sample
A BioWDL pipeline for processing RNA-seq data, starting with FASTQ files to produce expression measures and VCFs. Category:Multi-Sample
WDL implementation of the TALON workflow. Category:Multi-Sample InDevelopment
Worksheets to get started with the python software stack
lbcb-sci / graphmap2
Forked from isovic/graphmapGraphMap - A highly sensitive and accurate mapper for long, error-prone reads http://www.nature.com/ncomms/2016/160415/ncomms11307/full/ncomms11307.html https://www.biorxiv.org/content/10.1101/7204…
pycoQC computes metrics and generates Interactive QC plots from the sequencing summary report generated by Oxford Nanopore technologies basecaller (Albacore/Guppy)
A tool to identify, orient, trim and rescue full length cDNA reads
Full-Length Alternative Isoform analysis of RNA
Transcriptome Annotation by Modular Algorithms (for long read RNA sequencing data)
Miscellaneous collection of Python and R scripts for processing Iso-Seq data
Tool for the Quality Control of Long-Read Defined Transcriptomes
Iso-Seq - Scalable De Novo Isoform Discovery from Single-Molecule PacBio Reads
Lima - Demultiplex Barcoded PacBio Samples
CCS: Generate Highly Accurate Single-Molecule Consensus Reads (HiFi Reads)
🪼 a python library for doing approximate and phonetic matching of strings.
Official git repository for Biopython (originally converted from CVS)