sage
gatk4-genome-processing-pipeline-azure
sage | gatk4-genome-processing-pipeline-azure | |
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5 | 4 | |
197 | 7 | |
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7.7 | 0.0 | |
12 days ago | 2 months ago | |
Rust | wdl | |
MIT License | BSD 3-clause "New" or "Revised" License |
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sage
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Does anyone know a great guide/documentation explaining how to implement Percolator?
If you want to implement LDA from scratch, you could check out how Sage is doing it.
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What are some good examples of well-engineered bioinformatics pipelines?
You could check out https://github.com/lazear/sage - it's a near comprehensive program/pipeline for analyzing DDA/shotgun proteomics data. Most proteomics pipelines consist of running multiple, separate tools in sequence (search, spectrum rescoring, retention time prediction, quantification), but sage performs all of these. This cuts down on the need for disk space for storing intermediate results (none required), the need for IO (files are read once), and results in a proteomics pipeline that is >10-1000x faster than anything else, including commercial solutions
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Proteomics search engine written in Rust
You can also check out the intro blog post if you're interesting in learning more about the algorithm behind Sage. Beyond being fast, it also includes integrated machine learning (linear discriminant analysis, KDE) for rescoring spectral matches.
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Opinions on AlphaPept
You could try out Sage, if you're looking for speed - I don't think you'll find anything faster. https://github.com/lazear/sage
gatk4-genome-processing-pipeline-azure
- What are some good examples of well-engineered bioinformatics pipelines?
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Do you know how to get CNVs out of WES data sorted.bam files? (Free)
The GATK suite is pretty standard for calling germline mutations. Somatic mutation calling is a lot newer/trickier, so I'm just going to link to the GDC's practices.
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Best way to document tool?
This pre-processing pipeline from Microsoft (adapted from the Broad Institute/GATK) is pretty well-documented - at least in my opinion - with input requirements, expected outputs, software requirements, etc.
What are some alternatives?
rnaseq - RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.
juicer - A One-Click System for Analyzing Loop-Resolution Hi-C Experiments
seqkit - A cross-platform and ultrafast toolkit for FASTA/Q file manipulation
sv-callers - Snakemake-based workflow for detecting structural variants in genomic data
fasten - :construction_worker: Fasten toolkit, for streaming operations on fastq files
veba - A modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes
mokapot - Fast and flexible semi-supervised learning for peptide detection in Python
Rust-Bio - This library provides implementations of many algorithms and data structures that are useful for bioinformatics. All provided implementations are rigorously tested via continuous integration.
spades - SPAdes Genome Assembler