{"entity": "researcher", "timestamp": "2026-08-26T22:48:25.940Z", "family": "Friedrich", "given": "Stefanie", "initials": "S", "orcid": "0000-0002-3889-5589", "affiliations": ["Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, 17121, Solna, Sweden. stefanie.friedrich@scilifelab.se."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708"}}, "publications": [{"entity": "publication", "iuid": "f3963f48b95443f09aa70d6ad9494704", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f3963f48b95443f09aa70d6ad9494704.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f3963f48b95443f09aa70d6ad9494704"}}, "title": "Fusion transcript detection using spatial transcriptomics.", "authors": [{"family": "Friedrich", "given": "Stefanie", "initials": "S", "orcid": "0000-0002-3889-5589", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708.json"}}, {"family": "Sonnhammer", "given": "Erik L L", "initials": "ELL"}], "type": "journal article", "published": "2020-08-04", "journal": {"title": "BMC Med Genomics", "issn": "1755-8794", "volume": "13", "issue": "1", "pages": "110", "issn-l": "1755-8794"}, "abstract": "Fusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New high-throughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost single-cell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes.\n\nWe present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5' gene and has an elevated number of poly(A) tails for the 3' gene. Its expression level is defined by the upstream promoter of the 5' gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score.\n\nWe verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands.\n\nSTfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.", "doi": "10.1186/s12920-020-00738-5", "pmid": "32753032", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7437936"}, {"db": "pii", "key": "10.1186/s12920-020-00738-5"}], "notes": [], "created": "2026-08-20T12:20:28.236Z", "modified": "2026-08-20T12:20:28.273Z"}, {"entity": "publication", "iuid": "b8f0ba2dbbe44b229d7207f7b15399ee", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b8f0ba2dbbe44b229d7207f7b15399ee.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b8f0ba2dbbe44b229d7207f7b15399ee"}}, "title": "MetaCNV - a consensus approach to infer accurate copy numbers from low coverage data.", "authors": [{"family": "Friedrich", "given": "Stefanie", "initials": "S", "orcid": "0000-0002-3889-5589", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708.json"}}, {"family": "Barbulescu", "given": "Remus", "initials": "R"}, {"family": "Helleday", "given": "Thomas", "initials": "T"}, {"family": "Sonnhammer", "given": "Erik L L", "initials": "ELL"}], "type": "journal article", "published": "2020-06-01", "journal": {"title": "BMC Med Genomics", "issn": "1755-8794", "volume": "13", "issue": "1", "pages": "76", "issn-l": "1755-8794"}, "abstract": "The majority of copy number callers requires high read coverage data that is often achieved with elevated material input, which increases the heterogeneity of tissue samples. However, to gain insights into smaller areas within a tissue sample, e.g. a cancerous area in a heterogeneous tissue sample, less material is used for sequencing, which results in lower read coverage. Therefore, more focus needs to be put on copy number calling that is sensitive enough for low coverage data.\n\nWe present MetaCNV, a copy number caller that infers reliable copy numbers for human genomes with a consensus approach. MetaCNV specializes in low coverage data, but also performs well on normal and high coverage data. MetaCNV integrates the results of multiple copy number callers and infers absolute and unbiased copy numbers for the entire genome. MetaCNV is based on a meta-model that bypasses the weaknesses of current calling models while combining the strengths of existing approaches. Here we apply MetaCNV based on ReadDepth, SVDetect, and CNVnator to real and simulated datasets in order to demonstrate how the approach improves copy number calling.\n\nMetaCNV, available at https://bitbucket.org/sonnhammergroup/metacnv, provides accurate copy number prediction on low coverage data and performs well on high coverage data.", "doi": "10.1186/s12920-020-00731-y", "pmid": "32487140", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC7268502"}, {"db": "pii", "key": "10.1186/s12920-020-00731-y"}], "notes": [], "created": "2026-08-20T12:20:26.453Z", "modified": "2026-08-20T12:20:26.566Z"}, {"entity": "publication", "iuid": "8f040639969d42dd8f8a0b64ecaa1b5c", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/8f040639969d42dd8f8a0b64ecaa1b5c.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/8f040639969d42dd8f8a0b64ecaa1b5c"}}, "title": "MetaCNV - a consensus approach to infer accurate copy numbers from low coverage data", "authors": [{"family": "Friedrich", "given": "Stefanie", "initials": "S", "orcid": "0000-0002-3889-5589", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708.json"}}, {"family": "Barbulescu", "given": "Remus", "initials": "R"}, {"family": "Helleday", "given": "Thomas", "initials": "T"}, {"family": "Sonnhammer", "given": "Erik LL", "initials": "EL"}], "type": "posted-content", "published": "2020-02-04", "journal": {"issn-l": null}, "abstract": null, "doi": "10.21203/rs.2.15757/v2", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T12:57:39.183Z", "modified": "2026-08-20T12:57:39.202Z"}, {"entity": "publication", "iuid": "46b85e8cb5a54869802e671cbb06f377", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/46b85e8cb5a54869802e671cbb06f377.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/46b85e8cb5a54869802e671cbb06f377"}}, "title": "MetaCNV - a consensus approach to infer accurate copy numbers from low coverage data", "authors": [{"family": "Friedrich", "given": "Stefanie", "initials": "S", "orcid": "0000-0002-3889-5589", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3959b756f4334ba1a3b0536dbca15708.json"}}, {"family": "Barbulescu", "given": "Remus", "initials": "R"}, {"family": "Helleday", "given": "Thomas", "initials": "T"}, {"family": "Sonnhammer", "given": "Erik LL", "initials": "EL"}], "type": "posted-content", "published": "2019-10-07", "journal": {"issn-l": null}, "abstract": null, "doi": "10.21203/rs.2.15757/v1", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T12:57:37.444Z", "modified": "2026-08-20T12:57:37.458Z"}]}