aviary
sv-callers
aviary | sv-callers | |
---|---|---|
3 | 1 | |
68 | 71 | |
- | - | |
9.0 | 2.9 | |
8 days ago | 3 months ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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aviary
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what would you choose to detect specific genes in metagenomics data
Aviary is a good binning pipeline (there are others available), though perhaps more geared towards prokaryotes.
- Why bother reconstructing MAGs ?
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question about analysis of metagenome assembled genomes
Have a look at this especially the workflow figure https://github.com/rhysnewell/aviary
sv-callers
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Do you know how to get CNVs out of WES data sorted.bam files? (Free)
Generally, you have multiple ways to tackle this kind of a problem. For short read sequencing you have two types of CNV detection - readdepth based and paired-end based. CNVpytor (CNVnator) for example, is the former. You also have manta and lumpy. A lot of good pipelines use more than one SV caller and integrate them. For example: https://github.com/GooglingTheCancerGenome/sv-callers
What are some alternatives?
metaWRAP - MetaWRAP - a flexible pipeline for genome-resolved metagenomic data analysis
gatk4-genome-processing-pipeline-azure - Workflows used for processing whole genome sequence data + germline variant calling.
metaGEM - :gem: An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data
masurca
covalent - Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
zarp - The Zavolab Automated RNA-seq Pipeline
hecatomb - hecatomb is a virome analysis pipeline for analysis of Illumina sequence data
galaxy - Data intensive science for everyone.
SigProfilerExtractor - SigProfilerExtractor allows de novo extraction of mutational signatures from data generated in a matrix format. The tool identifies the number of operative mutational signatures, their activities in each sample, and the probability for each signature to cause a specific mutation type in a cancer sample. The tool makes use of SigProfilerMatrixGenerator and SigProfilerPlotting.