Data · dataset · 2026
Figure 1 from Improving Long-Read Somatic Structural Variant Calling with Pangenome and <i>De Novo</i> Personal Genome Assembly
Listed in ZivaHub
<p>Overview of somatic SV calling and filtering workflow.
Description
Minisv starts from the existing somatic SV call set. Step (1) Extract reads from somatic SVs in the tumor from the call set; (2) realign SV-containing reads to GRCh38, normal self-assembly (if available), and/or pangenome and extract candidate SVs from the realignment in the read coordinate; (3) compare the candidate SVs resulting from the alignment against multiple genomes; and (4) for each SV call set, extract supporting reads and filter a read if its alignment to the self-assembly and/or pangenome does not contain the SV.
Given multiple SV callers, minisv can generate a union somatic call set. Gray boxes denote the reference genome such as GRCh38; cyan boxes denote contigs from self-assembly; short red bars indicate potential somatic SVs; thin blue lines correspond to reads from the tumor aligned to the contigs of different reference genomes; thin orange lines correspond to reads from the normal control; and large brown circles indicate pangenome variant nodes that vary across individuals.</p>
Links
Where it is published
- DOI doi.org/10.1158/2767-9764.34022873 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
- From keywords
- Cancer · Computer Science & AI · Earth & Environmental Science · Life Sciences · Medicine & Health · Sequence analysis
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34022873 | 5 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[disease].local:disease:cancer | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['Cancer'] |
| concepts[field].anzsrc:field:310206 | mapping · zivahub uct ac za | vocabulary-mapper@1.0.0 | keywords['Sequence Analysis'] |
| concepts[field].local:field:computer-science-ai | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| description | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/description |
| license_text | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| publication_date | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | |
| title | source · zivahub uct ac za | connector:zivahub_uct_ac_za@1.0.0 | /metadata/dc/title |