25 skills found
broadinstitute / IchorCNAEstimating tumor fraction in cell-free DNA from ultra-low-pass whole genome sequencing.
nt246 / Physalia LcwgsFiles for the the Physalia course on Population genomic inference from low-coverage whole-genome sequencing data, Oct 10-13, 2022
xtmtd / PLWSPhylogenomics from Low-coverage Whole-genome Sequencing
ohlab / GRiDGrowth Rate Index (GRiD) measures bacterial growth rate from reference genomes (including draft quality genomes) and metagenomic bins at ultra-low sequencing coverage (> 0.2x).
sudmantlab / Loco Pipeloco-pipe is an automated Snakemake pipeline that streamlines a set of essential population genomic analyses for low-coverage whole genome sequencing (lcWGS) data
huangnengCSU / NanoSNPA deep learning-based SNP calling method to identify SNPs based on low-coverage Nanopore sequencing reads.
tgac-vumc / ACEAbsolute Copy Number Estimation using low-coverage whole genome sequencing data
Rosemeis / EmuEM-PCA for Ultra-low Coverage Sequencing Data
polyactis / AccucopyAccucopy is a computational method that infers Allele-Specific Copy Number alterations from low-coverage low-purity tumor sequencing data.
srubinacci / Imputation Ukb Ref PanelGenotype imputation pipelines for the UK Biobank Research Analysis Platform
winni2k / GLPhaseA tool for phasing and imputing haplotypes in 10k+ low coverage sequencing samples
Zilong-Li / LcWGS Imputation WorkflowImputation workflow for low coverage whole genome sequencing data
karinkumar / MetaGLIMPSEMeta Imputation of Low Coverage Sequencing
mgdesaix / WGSassignPopulation assignment from genotype likelihoods for low-coverage whole-genome sequencing data
asylvz / CONGACONGA: COpy Number Genotyping in Ancient genomes and low-coverage sequencing data
Zilong-Li / BaseVarCThe repo was not under active development. Check out angsd toolkit for low depth data analyses.
hirzi / WorkshopMRIN workshop for inferring population structure, summary statistics and selection from low-coverage whole-genome sequencing (WGS) data
cguyomar / PARSECVariant calling and imputation from low coverage sequencing data
Paleogenomics / IBDGemProgram for positive genetic identification and IBD detection from low-coverage sequencing data
timnat / DifCoverThe DifCover pipeline aims to identify regions in a reference genome for which the read coverage of a sample1 to the reference is significantly different from the read coverage of a sample2. “Significantly different” is determined by user defined threshold on a ration between average coverages of given samples. The pipeline allows to exclude from a consideration the under-represented fragments (with low coverage in sequencing of both samples) and/or the regions that carry repetitive sequences. Both cases can be misleading in the coverage analysis. The DifCover pipeline is specifically oriented to the analysis of large genomes and can handle very fragmented assemblies.
