Sandve group
The group is involved in several projects and collaborations within statistical genomics, comparative genomics, epigenetic epidemiology and immune receptor informatics
Research aims
- Through a collaboration between computer scientists, statisticians and biologists having lasted more than a decade, we have been heavily involved in the development of statistical methodology and a software platform for genomic colocalization analysis. A large variety of experimental assays can at present be combined with high throughput sequencing and read mapping to produce sets of genomic regions as a main output. The resulting unified representation of diverse omics features as reference genome coordinates provides a very powerful basis for integrative omics.
We believe there is a large untapped potential related to genomic colocalization analysis, and aim to spearhead the development of improved generic analysis methodology, with a particular focus on epidemiological and comparative genomics settings. - Through several ongoing projects and collaborations, we aim to delineate and model how the receptor sequence determines which antigens are recognized by a given B or T cell. This is approached by characterizing statistical dependencies and compositional features of receptor sequences, and using this to guide the development of machine learning methods for detecting disease states of a patient's immune repertoire as an early diagnostic.
This methodological inquiry is combined with the development of a robust software platform ImmuneML that allows both novices and experts to perform immune repertoire analyses in an efficient and reproducible manner.
Research topics
- Comparative genomics
- Genome dynamics
- Epigenetic epidemiology (PharmaTox)
- Comparative genomics (CELS)
- Immune receptor characterization (ImmunoLingo)
People
- Geir Kjetil Sandve (PI)
- Boris Simovsky (PhD student)
- Ivar Grytten (PhD student)
- Milena Pavlovic (PhD student)
- Stefania Salvatore (postdoc)
We also have several associate members in the group:
- Ralf Stefan Neumann (postdoc, dual association with Ludvig Sollid)
- Ankush Sharma (postdoc, dual association with Odd Stokke Gabrielsen, Ragnhild Eskeland and Eivind Hovig)
- Knut Rand (co-supervised with Ingrid Glad, Lex Nederbragt, Geir Storvik)
- Ying Yao (co-supervised with Shuo-Wang Qiao)
- Ksenia Khelik (co-supervised with Torbjørn Rognes, Lex Nederbragt)
- Daniel Vodàk (co-supervised with Eivind Hovig, Sigve Nakken)
Software
Publications
Publications 2020
T cell receptor repertoire as a potential diagnostic marker for celiac disease
Clin Immunol, 222, 108621 (in press)
DOI 10.1016/j.clim.2020.108621, PubMed 33197618
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
Bioinformatics, 36 (11), 3594-3596
DOI 10.1093/bioinformatics/btaa158, PubMed 32154832
Assessing graph-based read mappers against a baseline approach highlights strengths and weaknesses of current methods
BMC Genomics, 21 (1), 282
DOI 10.1186/s12864-020-6685-y, PubMed 32252628
Author Correction: Human somatic cell mutagenesis creates genetically tractable sarcomas
Nat Genet, 52 (4), 464
DOI 10.1038/s41588-020-0589-2, PubMed 32094913
NucBreak: location of structural errors in a genome assembly by using paired-end Illumina reads
BMC Bioinformatics, 21 (1), 66
DOI 10.1186/s12859-020-3414-0, PubMed 32085722
B cell tolerance and antibody production to the celiac disease autoantigen transglutaminase 2
J Exp Med, 217 (2)
DOI 10.1084/jem.20190860, PubMed 31727780
Publications 2019
A map of direct TF-DNA interactions in the human genome
Nucleic Acids Res, 47 (14), 7715
DOI 10.1093/nar/gkz582, PubMed 31251803
Augmenting adaptive immunity: progress and challenges in the quantitative engineering and analysis of adaptive immune receptor repertoires
Mol. Syst. Des. Eng., 4 (4), 701-736
Transcriptional profiling of human intestinal plasma cells reveals effector functions beyond antibody production
United European Gastroenterol J, 7 (10), 1399-1407
DOI 10.1177/2050640619862461, PubMed 31839965
Colocalization analyses of genomic elements: approaches, recommendations and challenges
Bioinformatics, 35 (9), 1615-1624
DOI 10.1093/bioinformatics/bty835, PubMed 30307532
A map of direct TF-DNA interactions in the human genome
Nucleic Acids Res, 47 (4), e21
DOI 10.1093/nar/gky1210, PubMed 30517703
Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes
PLoS Comput Biol, 15 (2), e1006731
DOI 10.1371/journal.pcbi.1006731, PubMed 30779737
Publications 2018
Mind the gaps: overlooking inaccessible regions confounds statistical testing in genome analysis
BMC Bioinformatics, 19 (1), 481
DOI 10.1186/s12859-018-2438-1, PubMed 30547739
Exploiting antigen receptor information to quantify index switching in single-cell transcriptome sequencing experiments
PLoS One, 13 (12), e0208484
DOI 10.1371/journal.pone.0208484, PubMed 30517183
Coloc-stats: a unified web interface to perform colocalization analysis of genomic features
Nucleic Acids Res, 46 (W1), W186-W193
DOI 10.1093/nar/gky474, PubMed 29873782
Disease-driving CD4+ T cell clonotypes persist for decades in celiac disease
J Clin Invest, 128 (6), 2642-2650
DOI 10.1172/JCI98819, PubMed 29757191
Publications 2017
Complex patterns of concomitant medication use: A study among Norwegian women using paracetamol during pregnancy
PLoS One, 12 (12), e0190101
DOI 10.1371/journal.pone.0190101, PubMed 29284043
Genome build information is an essential part of genomic track files
Genome Biol, 18 (1), 175
DOI 10.1186/s13059-017-1312-1, PubMed 28911336
Uracil Accumulation and Mutagenesis Dominated by Cytosine Deamination in CpG Dinucleotides in Mice Lacking UNG and SMUG1
Sci Rep, 7 (1), 7199
DOI 10.1038/s41598-017-07314-5, PubMed 28775312
NucDiff: in-depth characterization and annotation of differences between two sets of DNA sequences
BMC Bioinformatics, 18 (1), 338
DOI 10.1186/s12859-017-1748-z, PubMed 28701187
GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome
Gigascience, 6 (7), 1-12
DOI 10.1093/gigascience/gix032, PubMed 28459977
High-Throughput Single-Cell Analysis of B Cell Receptor Usage among Autoantigen-Specific Plasma Cells in Celiac Disease
J Immunol, 199 (2), 782-791
DOI 10.4049/jimmunol.1700169, PubMed 28600290
The rainfall plot: its motivation, characteristics and pitfalls
BMC Bioinformatics, 18 (1), 264
DOI 10.1186/s12859-017-1679-8, PubMed 28521741
Coordinates and intervals in graph-based reference genomes
BMC Bioinformatics, 18 (1), 263
DOI 10.1186/s12859-017-1678-9, PubMed 28521770
Publications 2016
Galaxy Portal: interacting with the galaxy platform through mobile devices
Bioinformatics, 32 (11), 1743-5
DOI 10.1093/bioinformatics/btw042, PubMed 26819474
Publications 2015
In the loop: promoter-enhancer interactions and bioinformatics
Brief Bioinform, 17 (6), 980-995
DOI 10.1093/bib/bbv097, PubMed 26586731
c-Myb Binding Sites in Haematopoietic Chromatin Landscapes
PLoS One, 10 (7), e0133280
DOI 10.1371/journal.pone.0133280, PubMed 26208222
ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets
PLoS One, 10 (4), e0123261
DOI 10.1371/journal.pone.0123261, PubMed 25879845
EBNA2 binds to genomic intervals associated with multiple sclerosis and overlaps with vitamin D receptor occupancy
PLoS One, 10 (4), e0119605
DOI 10.1371/journal.pone.0119605, PubMed 25853421
Transcriptionally active regions are the preferred targets for chromosomal HPV integration in cervical carcinogenesis
PLoS One, 10 (3), e0119566
DOI 10.1371/journal.pone.0119566, PubMed 25793388
Monte Carlo Null Models for Genomic Data
Stat. Sci., 30 (1), 59-71
Publications 2014
Human somatic cell mutagenesis creates genetically tractable sarcomas
Nat Genet, 46 (9), 964-72
DOI 10.1038/ng.3065, PubMed 25129143
Chromatin states reveal functional associations for globally defined transcription start sites in four human cell lines
BMC Genomics, 15, 120
DOI 10.1186/1471-2164-15-120, PubMed 24669905
HiBrowse: multi-purpose statistical analysis of genome-wide chromatin 3D organization
Bioinformatics, 30 (11), 1620-2
DOI 10.1093/bioinformatics/btu082, PubMed 24511080
Publications 2013
Integrating multiple oestrogen receptor alpha ChIP studies: overlap with disease susceptibility regions, DNase I hypersensitivity peaks and gene expression
BMC Med Genomics, 6, 45
DOI 10.1186/1755-8794-6-45, PubMed 24171864
Ten simple rules for reproducible computational research
PLoS Comput Biol, 9 (10), e1003285
DOI 10.1371/journal.pcbi.1003285, PubMed 24204232
Vitamin D receptor ChIP-seq in primary CD4+ cells: relationship to serum 25-hydroxyvitamin D levels and autoimmune disease
BMC Med, 11, 163
DOI 10.1186/1741-7015-11-163, PubMed 23849224
The Genomic HyperBrowser: an analysis web server for genome-scale data
Nucleic Acids Res, 41 (Web Server issue), W133-41
DOI 10.1093/nar/gkt342, PubMed 23632163
Handling realistic assumptions in hypothesis testing of 3D co-localization of genomic elements
Nucleic Acids Res, 41 (10), 5164-74
DOI 10.1093/nar/gkt227, PubMed 23571755
Publications 2012
Vitamin D receptor binding, chromatin states and association with multiple sclerosis
Hum Mol Genet, 21 (16), 3575-86
DOI 10.1093/hmg/dds189, PubMed 22595971
Age-associated hyper-methylated regions in the human brain overlap with bivalent chromatin domains
PLoS One, 7 (9), e43840
DOI 10.1371/journal.pone.0043840, PubMed 23028473
Genomic regions associated with multiple sclerosis are active in B cells
PLoS One, 7 (3), e32281
DOI 10.1371/journal.pone.0032281, PubMed 22396755
Publications 2011
Identifying elemental genomic track types and representing them uniformly
BMC Bioinformatics, 12, 494
DOI 10.1186/1471-2105-12-494, PubMed 22208806
Sequential Monte Carlo multiple testing
Bioinformatics, 27 (23), 3235-41
DOI 10.1093/bioinformatics/btr568, PubMed 21998154
Increased expression of IRF4 and ETS1 in CD4+ cells from patients with intermittent allergic rhinitis
Allergy, 67 (1), 33-40
DOI 10.1111/j.1398-9995.2011.02707.x, PubMed 21919915
The differential disease regulome
BMC Genomics, 12, 353
DOI 10.1186/1471-2164-12-353, PubMed 21736759
Publications 2010
The Genomic HyperBrowser: inferential genomics at the sequence level
Genome Biol, 11 (12), R121
DOI 10.1186/gb-2010-11-12-r121, PubMed 21182759
Publications 2008
Segmentation of DNA sequences into twostate regions and melting fork regions
J Phys Condens Matter, 21 (3), 034109
DOI 10.1088/0953-8984/21/3/034109, PubMed 21817254
Compo: composite motif discovery using discrete models
BMC Bioinformatics, 9, 527
DOI 10.1186/1471-2105-9-527, PubMed 19063744