====== Journal club ======

This page has grown too big and includes two pieces:
  - info on previous and future journal club sessions held by biostats group. See below for the timetable for the Journal Club 2022. Please contact Guy (g.f.l.hindley@medisin.uio.no) if you have any questions.  
  - other "learning" info relevant to the members of the biostats team:
    * the list and agenda of past Journal Club seminars
    * the list of papers discussed at the Journal Club, and those that are relevant to the biostats group
    * the list of youtube  recordings / channels relevant to the biostats group
    * the list of relevant conferences 

See 'table of contents' panel on the right-hand side to navigate through this page.

====== Papers ======

MiXeR models

  * univariate https://pubmed.ncbi.nlm.nih.gov/32427991/
  * bivariate https://pubmed.ncbi.nlm.nih.gov/31160569/
  * extended https://pubmed.ncbi.nlm.nih.gov/33789345/
 
Multivariate models for imaging genetics

  * https://pubmed.ncbi.nlm.nih.gov/32665545/
 
Conditional FDR approach

  * https://pubmed.ncbi.nlm.nih.gov/31520123/
 
Large scale gene discovery applying novel stats tools

  * https://pubmed.ncbi.nlm.nih.gov/34160554/
  * https://pubmed.ncbi.nlm.nih.gov/34006833/
 
Conceptual review:

  * https://pubmed.ncbi.nlm.nih.gov/32528109/

====== GWAS course materials (with videos) =======

The following link has resources and video recordings from the past GWAS course held by the biostats team and our collaborators. See below for agenda of the course (GWAS course 2021, link for 2022 GWAS course see below).

https://uio-my.sharepoint.com/:f:/g/personal/alexeas_uio_no/EgIRbDoGFBJJsX2lm-xSAcwBoOXCw5qFSeY6FXscViUPKQ?e=MGEhqK

Day 1 [22.03]. Genome-wide association studies background and clinical implications.

  * 09:30 – 09:45	General introduction and overview of projects in NORMENT. [Ole Andreassen]
  * 09:45 – 10:45	Genes, genomes and genetic variation. [Timothy Hughes]
  * 10:50– 11:35	GWAS. Clinical implications. [Romain Icick]
  * 12:05 – 13:30	Preparing for workshops. [Alexey Shadrin]

Day 2 [23.03]. Pre-GWAS: quality control and imputation.

  * 09:30 – 10:00	Genotyping. Quality control (QC) with GenomeStudio. [Lavinia Andresen]
  * 10:00 – 10:45	Pre-imputation QC, imputation and post-imputation QC + workshop (part 1). [Elizabeth Corfield]
  * 10:50 – 11:35	Pre-imputation QC, imputation and post-imputation QC + workshop (part 2). [Elizabeth Corfield]
  * 12:05 – 13:00	Brain imaging and genetics. [Thomas Wolfers]

Day 3 [24.03]. GWAS essentials: association testing, annotation of the results and available resources.
  * 09:30 – 10:30	Testing for association, meta-analysis and interpretation of the results + workshop. [Alexey Shadrin]
  * 10:35 – 11:35	Survey of available GWAS data. Overview of TSD. [Oleksandr Frei]
  * 11:35 – 12:05	Lunch Break.
  * 12:05 – 12:50	FUMA, pathway and network analysis + workshop. [Shahram Bahrami]
  * 12:50 – 13:35	Heritability concept and misconceptions. Genetic architecture beyond heritability. [Francesco Bettella]

Day 4 [25.03]. Post-GWAS analyses.

  * 09:30 – 10:30	Polygenic risk scores + workshop. [Alexey Shadrin]
  * 10:35 – 11:35	LD-score regression and genetic correlation + workshop. [Oleksandr Frei]
  * 12:05 – 12:50	Advanced polygenic prediction approaches. [Ehsan Motazedi]
  * 12:50 – 13:35	Concluding remarks, discussion and distribution of examination tasks.

Other resources on GWAS:

  * a paper with basic introduction to GWAS: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531285/
  * Another GWAS course: https://www.mv.helsinki.fi/home/mjxpirin/GWAS_course/
  * GWAS course 2022 version: https://uio-my.sharepoint.com/personal/alexeas_uio_no/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Falexeas%5Fuio%5Fno%2FDocuments%2Fprojects%2Fgwas%5Fcourse%2Fnorment%5Fcourse%5F2022%2Fshared%5Fmaterials&ga=1

====== Youtube and other dissemination videos ====== 

Not all vides are available on the internet. If you have access to NIRD, see recordings here: /projects/NS9114K/biostats/recordings.

  * NSHG-PM Webinar (by Ole Andreassen, Oleksandr Frei): Polygenic Architecture of Mental Traits and Disorders: Are Small Effects the New Normal? [[https://youtu.be/66tXR3D3bus|link]]
  * AI@MIPT: «Using big data for mathematical models of the human genome — implications for psychiatric genetics» (by Kevin O'Connell, Oleksandr Frei) [[https://vk.com/aimipt?z=video-932_456239307%2Fd696f349787cbdc234%2Fpl_wall_-155341956​|link]]
  * Introduction to MiXeR (Oleksandr Frei): https://youtu.be/cEASkzjJ_F0
  * Mathematical Models of the Genetic Architecture in Complex Human Disorders (by Oleksandr[[https://www.youtube.com/watch?v=t-LtwviH4zY&feature=youtu.be​|link]]
  * Applying novel statistical approaches in neuroimaging and psychiatric genetics  (by Oleksandr[[http://cnbr.skoltech.ru/openeducation/alex_frei|link]]

Other videos on relevant methods in statistical genetics:

 * https://www.youtube.com/playlist?list=PLnJh2XY-rMTnOdlGMEUgJfoS_Uu9Qcun0 (E.g. watch [[https://www.youtube.com/watch?v=Q2VR1iL4l9o&list=PLnJh2XY-rMTnOdlGMEUgJfoS_Uu9Qcun0&index=5|here]] from min 37 to 49 to learn about HDL ( https://github.com/zhenin/HDL ) 
    
====== Biostats Knowledge transfer videos (Feb 2020) ======

https://1drv.ms/u/s!AowdZ5fcU7BRhftpAqxvTyZu-7sdCA?e=N2U91N - protected by password **RSquared**

Agenda:
<code>
Mon Feb 10 - 10 AM - Kevin           - projects overview, ​introduction to GWAS methodology,
                                       PGC consortia and data access;
Tue Feb 11 - 10 AM - Alex            - hands-on inro to infrastructure (NORMENT wiki, github, TSD, NIRD, SAGA),
                                       External data access (Summary Statistics, UK Biobank); 
Wed Feb 12 - 10 AM - Lavinia         - NORMENT and MoBa data;
Thu Feb 13 - 10 AM - Francesco       - NORMENT bioinformatics service & imputation pipeline;
Fri Feb 14 - 10 AM - Shahram         - projects overview, pleioFDR tool, overview of FUMA;
Mon Feb 17 - 10 AM - Alexey          - polygenic risks cores, AI MiXeR, LD Score Regression, methods development;
​Wed Feb 19 - 10 AM ​​- Olav and/or Naz - projects overview, what do we know about Schizophrenia,
                                       conditional/conjunctive FDR for epilepsy;
Thu Feb 20 - 10 AM - Alex            - Cross-Trait MiXeR and MOSTest projects (heavy math day).
                                       (or, continue more with infrastructure)
</code>


====== Conferences =====

  * WCPG : https://ispg.net/wcpg-2021/
  * ASHG : https://www.ashg.org/meetings/2021meeting/
  * EMGM : https://wp.unil.ch/emgm2020/
  * others?


====== Journal club sessions 2022-2023 =====

  * 26.08.2022 - Kevin
  * 09.09.2022 - Borge
  * 23.09.2022 – Elise

Autumn Holiday

  * 14.10.2022 - Vera
  * 28.10.2022 - Pravesh
  * 11.11.2022 - Markos
  * 25.11.2022 - Espen
  * 02.12.2022 - Sandeep
  * 16.12.2022 – Linn

Christmas Holiday

  * 06.01.2023 - Guy
  * 20.01.2023 - Weiqiu
  * 03.02.2023 - Nadine
  * 17.02.2023 - Olav
  * 03.03.2023 – Zillur
  * 17.03.2023 - Gleda
  * 31.03.2023 - Piotr

Easter Holiday

  * 14.04.2023 - Alexey
  * 28.04.2023 - Evgeniia
  * 12.05.2023 - Viktoria
  * 26.05.2023 - Nora
  * 09.06.2023 - Tahir
  * 23.06.2023 - Naz

====== Journal club sessions 2021-2022 =====

March 18th - Sandeep
  * Deep neural networks in psychiatry - https://www.nature.com/articles/s41380-019-0365-9 
  * {{:biostat:biostats_journal_club_sandeep.pptx|}}

March 4th - Olav
  * Mapping SNPs to genes - {{:biostat:olav_snps_to_genes_040322.pptx|}}

February 18th - Guy
  * Saturated GWAS of height - https://www.biorxiv.org/content/10.1101/2022.01.07.475305v1.full.pdf
  * {{:biostat:guy_height_gwas_180222.pptx|}}

January 28th - Markos
  * Methylation Risk Scores {{:biostat:methylation_rs.pdf|}}

January 14th - Nora
  * MoBa project planning

Friday 22nd January – Guy 
  * A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior
  * https://www.nature.com/articles/s41380-020-0777-6

Friday 5th Feb – Alexey
  * Convergence of placenta biology and genetic risk for schizophrenia
  * https://www.nature.com/articles/s41591-018-0021-y

Friday 19th February – MiXeR and conjFDR conceptual overview
  * Zoom recording on nird (/nird/projects/NS9114K/biostats/recordings)
  * ppt slides: {{:biostat:mixer_and_pleiofdr.pptx|}}
  * https://www.nature.com/articles/s41467-019-10310-0

Friday 19th March – Srdjan - Maternal immune activation in mice disrupts
proteostasis in the fetal brain
  * https://pubmed.ncbi.nlm.nih.gov/33361822/

EASTER

Friday 16th April – Yunhan - novelty checking procedure

Friday 30th April – Kevin - genetic overlap without genetic correlation: can sub-groups explain co-morbidity?
{{:biostat:kevn_journal_club_presentation.pptx|}}

Friday 28th May – Nadine Parker - Mendelian randomisation {{:biostat:Mendelian_Randomization.pptx|}}

SUMMER HOLIDAY

Friday 10th September - Aihua Lin - Multivariate GWAS methods https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0095923

Friday 24th September – Børge - Psilocybin for treatment resistant depression
https://www.nejm.org/doi/10.1056/NEJMoa2032994?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed

October 8th  – Weiqiu - Integrative functional genomic analysis of human brain development and neuropsychiatric risks (PsychEncode)
https://pubmed.ncbi.nlm.nih.gov/30545854/

October 22nd  – Nora - MoBa Masterclass
{{:biostat:moba-basics_journalclub211022.pptx|}}

November 5th – Romain - Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction
[[https://www.nature.com/articles/s41593-021-00908-3]]

November 19th – Alex/Nadine/Alexey- Mixed effects models
[[https://docs.google.com/presentation/d/1p5cBPFQzAKz9vsVg6zHN4nlfaRrhViVgbJBwPXuNHOU/edit#slide=id.p]]

===== Future ideas =====
New pipeline for summary statistics
How to use the singularity containers

Please contribute to this page by adding papers that you've found particularly useful - both from our group, and external.


====== More Papers ======


** Conditional/conjunctional False Discovery Rate **
  * Andreassen, O. A. et al. Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors. Am. J. Hum. Genet. 92, 197–209 (2013).
  * Andreassen, O. A. et al. Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate. PLoS. Genet. 9, e1003455 (2013).
  * Smeland, O. B. et al. Identification of genetic loci jointly influencing schizophrenia risk and the cognitive traits of verbal-numerical reasoning, reaction time, and general cognitive function. JAMA Psychiatry 74, 1065–1075 (2017).
  * Smeland, O.B., et al., Discovery of shared genomic loci using the conditional false discovery rate approach. Hum Genet, 2019.


** GWAS papers **
  * Schizophrenia Working Group of the Psychiatric Genomics, C. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).
  * Stahl E. A. et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat. Genet. 51, 793–803 (2019)
  * Ruderfer, D. M. et al. Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes. Cell 173, 1705–1715.e16 (2018).
  * International League Against Epilepsy Consortium on Complex, E., Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies. Nat Commun, 2018. 9(1): p. 5269.
  * Brainstorm, C., et al., Analysis of shared heritability in common disorders of the brain. Science, 2018. 360(6395).
  * Cross-Disorder Group of the Psychiatric Genomics Consortium, L.e.a., Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Unpublished, 2019. https://doi.org/10.1101/528117
  * Zhiyu Yang, H.W., Phil H. Lee et al., Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome. Unpublished, 2019. https://doi.org/10.1101/770222 
  * Demontis, D., et al., Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet, 2019. 51(1): p. 63-75.
  * Grove, J., et al., Identification of common genetic risk variants for autism spectrum disorder. Nat Genet, 2019. 51(3): p. 431-444.
  * Wray, N.R., et al., Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet, 2018. 50(5): p. 668-681.
  * Howard, D.M., et al., Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci, 2019. 22(3): p. 343-352.
  * Howard, D.M., et al., Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat Commun, 2018. 9(1): p. 1470.
  * Lee, S., Ripke, S., Neale, B. et al. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet 45, 984–994 (2013) doi:10.1038/ng.2711
  * Skene N.G., et al., Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Genetic identification of brain cell types underlying schizophrenia, Nat. Genet., 50 (2018), pp. 825-833


** Reviews **
  * Freitag, C.M., The genetics of autistic disorders and its clinical relevance: a review of the literature. Mol Psychiatry, 2007. 12(1): p. 2-22.
  * Tam, V., Patel, N., Turcotte, M. et al. Benefits and limitations of genome-wide association studies. Nat Rev Genet 20, 467–484 (2019) doi:10.1038/s41576-019-0127-1
  * Visscher, P.M., et al., 10 Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet, 2017. 101(1): p. 5-22.
  * Gallagher, M.D., Chen-Plotkin, A.S. The Post-GWAS Era: From Association to Function. Am J Hum Genet. 2018 May 3;102(5):717-730. doi: 10.1016/j.ajhg.2018.04.002. 
  * Docherty, A.R., Moscati, A.A. & Fanous, A.H. Cross-Disorder Psychiatric Genomics. Curr Behav Neurosci Rep (2016) 3: 256. https://doi.org/10.1007/s40473-016-0084-3
  * Sullivan, P.F., Geschwind, D.H., Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders, Cell, Vol 177, Issue 1, 2019, Pages 162-183, ISSN 0092-8674, https://doi.org/10.1016/j.cell.2019.01.015.

** Methods **
  * Holland, D. et al. Estimating degree of polygenicity, causal effect size variance, and confounding bias in GWAS summary statistics. Preprint at bioRxiv https://doi.org/10.1101/133132 (2017).
  * Schork, A. J. et al. All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs. PLoS. Genet. 9, e1003449 (2013).
  * Frei, O. et al. Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation. Nat. Commun. 10, 2417 (2019).
  * Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
  * Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).
  * Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
  * Hou, K., et al., Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture. Nat Genet, 2019. 51(8): p. 1244-1251.
  * Dominic Holland, O.F., Rahul Desikan, Chun-Chieh Fan, Alexey A. Shadrin, Olav B. Smeland, V. S. Sundar, Paul Thompson, Ole A. Andreassen, Anders M. Dale, Beyond SNP Heritability: Polygenicity and Discoverability of Phenotypes Estimated with a Univariate Gaussian Mixture Model. Unpublished, 2019. https://doi.org/10.1101/133132
  * Watanabe, K., et al., Functional mapping and annotation of genetic associations with FUMA. Nat Commun, 2017. 8(1): p. 1826.


** Other **
  * Allsopp, K., et al., Heterogeneity in psychiatric diagnostic classification. Psychiatry Res, 2019. 279: p. 15-22.
  * Smoller, J.W. and C.T. Finn, Family, twin, and adoption studies of bipolar disorder. Am J Med Genet C Semin Med Genet, 2003. 123C(1): p. 48-58.
  * Sullivan, P.F., K.S. Kendler, and M.C. Neale, Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry, 2003. 60(12): p. 1187-92.
  * Sullivan, P.F., M.C. Neale, and K.S. Kendler, Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry, 2000. 157(10): p. 1552-62.
  * Kjeldsen, M.J., et al., Genetic and environmental factors in epilepsy: a population-based study of 11900 Danish twin pairs. Epilepsy Res, 2001. 44(2-3): p. 167-78.
  * Brooks-Kayal, A.R., et al., Issues related to symptomatic and disease-modifying treatments affecting cognitive and neuropsychiatric comorbidities of epilepsy. Epilepsia, 2013. 54 Suppl 4: p. 44-60.

Please add more papers!


