| brentp/mosdepth |
617 |
|
0 |
0 |
over 2 years ago |
0 |
|
49 |
mit |
Nim |
| fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing |
| KamilSJaron/smudgeplot |
200 |
|
0 |
0 |
about 2 years ago |
0 |
|
19 |
apache-2.0 |
R |
| Inference of ploidy and heterozygosity structure using whole genome sequencing data |
| sequana/sequana |
136 |
|
6 |
11 |
over 2 years ago |
111 |
March 01, 2026 |
12 |
bsd-3-clause |
Jupyter Notebook |
| Sequana: a set of Snakemake NGS pipelines |
| odelaneau/GLIMPSE |
110 |
|
0 |
0 |
over 2 years ago |
0 |
|
22 |
mit |
C++ |
| Low Coverage Calling of Genotypes |
| zstephens/neat-genreads |
72 |
|
0 |
0 |
over 4 years ago |
0 |
|
25 |
other |
Python |
| NEAT read simulation tools |
| human-pangenomics/HG002_Data_Freeze_v1.0 |
54 |
|
0 |
0 |
almost 4 years ago |
0 |
|
1 |
|
|
| Human Pangenome Reference Consortium - HG002 Data Freeze (v1.0) |
| RCollins13/CNView |
50 |
|
0 |
0 |
over 8 years ago |
0 |
|
3 |
mit |
R |
| Visualization and annotation of CNVs from population-scale whole-genome sequencing data |
| Clinical-Genomics/chanjo |
48 |
|
0 |
0 |
over 2 years ago |
0 |
|
40 |
mit |
Python |
| Chanjo provides a better way to analyze coverage data in clinical sequencing. |
| nt246/physalia-lcwgs |
43 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
|
HTML |
| Files for the the Physalia course on Population genomic inference from low-coverage whole-genome sequencing data, Oct 10-13, 2022 |
| diriano/ploidyNGS |
35 |
|
0 |
0 |
about 3 years ago |
0 |
|
1 |
gpl-3.0 |
HTML |
| Explore ploidy levels from NGS data alone |
