Rigor and Reproducibility in Genetics and Genomics: Peer-reviewed, Published,

Description: Section 1: Introduction 1. Review of reproducibility in genetic studies John Ioannidis, PhD 2. Review of common statistical practices and assumptions Daniel Benjamin, PhD 3. Rigor in the classroom and in the mentor/mentee relationship Douglas F. Dluzen, PhD Section 2: Genotyping 4. Review of GWAS studies Naomi Wray, PhD 5. Best practices in GWAS and pitfalls to avoid Daniel Benjamin, PhD 6. GWAS learning and training activities Bethany Bowling, PhD, Northern Kentucky University 7. DNA sequencing for genotyping and best practices for comparative genomics Heidi Rehm, PhD 8. Statistical approaches for rigorous genome sequence analyses and genotype imputations Nianjun Liu, PhD, Indiana University 9. DNA sequencing activities; classroom case studies Rivka Glaser, PhD, Stevenson University Section 3: Gene Expression 10. Review of gene expression using microarray and RNA-seq Alexandra Soboleva 11. Best statistical approaches for analysis of gene expression data Purvesh Katri, PhD 12. Validating approaches to gene expression studies Yaov Benjamin, PhD 13. Misconceptions in the classroom and case studies Dina Newman, PhD Section 4: Epigenetic Analyses 14. Review of DNA methylation and other omits data resources Thomas Jenuwein 15. Statistical approaches to improve rigor in Chip-Seq, methyl-seq, and epi datasets Olga Troyanskaya, PhD 16. Best methods for combining DNA, RNA, and methylation data Jennie Williams, PhD 17. Teaching epigenetics in the classroom Louisa Stark, PhD Section 5: Gene Editing Technologies 18. Review of current gene editing technologies, including CRISPR Lei Stanley Qi, PhD 19. Best strategies to design and implement CRISPR-based genetic analysis Kathy Niakan, Phd 20. CRISPR classroom activities and/or case studies Sylvain Moineau, PhD Section 6: Conclusion Appendix: Links to supplementary resources

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