SigProfilerExtractor
sv-callers
| SigProfilerExtractor | sv-callers | |
|---|---|---|
| 1 | 1 | |
| 146 | 71 | |
| 2.7% | - | |
| 3.5 | 2.9 | |
| 16 days ago | 3 months ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | Apache License 2.0 |
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SigProfilerExtractor
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Any good tutorials/guides for cancer mutation analysis?
Ludmil Alexandrov's tools may be a better modern choice for real data though: https://github.com/AlexandrovLab/SigProfilerExtractor
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?
deepvariant - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
gatk4-genome-processing-pipeline-azure - Workflows used for processing whole genome sequence data + germline variant calling.
scispacy - A full spaCy pipeline and models for scientific/biomedical documents.
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
Biopython - Official git repository for Biopython (originally converted from CVS)
covalent - Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
scanpy - Single-cell analysis in Python. Scales to >1M cells.
aviary - A hybrid assembly and MAG recovery pipeline (and more!)
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.