DeepSelecNet is an enhanced deep learning model to perform read classification for selective sequencing.
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Updated
Mar 5, 2023 - C
DeepSelecNet is an enhanced deep learning model to perform read classification for selective sequencing.
Ampseer examines reads in fastq format and identifies which multiplex PCR primer set was used to generate the SARS-CoV-2 sequencing library they are read from. It is intended to differentiate between ARTIC v3, ARTIC v4, ARTIC v4.1, VarSkip 1a, VarSkip 2, Midnight and VarSkip Long primer sets sequenced by Illumina or ONT.
NGSphy: phylogenomic simulation of next-generation sequencing data
This repository contains the code to run the ASCETS arm-level copy number events caller for targeted sequencing data. ASCETS produces arm-level copy-number variant calls and arm-level weighted average log2 segment means from segmented copy number data.
Targeted Amplicon Bisulfite Sequencing Analysis Tool
Identification of gene-fusions, including EML4-ALK
A reproducible and scalable snakemake workflow for the analysis of DNA metabarcoding experiments, with a special focus on food and feed samples.
Create a normalized heatmap for targeted RNAseq count matrix using user-defined housekeeping gene normalization.
Targeted RNA-sequencing for the quantification of measurable residual disease in acute myeloid leukemia
Tools for analyzing UMIErrorCorrect output
Coverage analysis of the data from the targeted-sequencing experiment of Hummingbirds (data from the paper Fonseca et al. 2018)
pyAmpli: an amplicon-based variant filter pipeline for targeted enriched resequencing data
A Snakemake pipeline for copy number variant calling without normal tissue samples
For simulations of targeted-sequencing experiments under a known species/gene tree distribution, extracts the reference sequences that be used for mapping.
MSKCC CMO Innovation Lab
Barcode Analyzer for metabarcoding experiments
🍃 🧬 🧹 Probe set cleaning (Melastomataceae)
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