├── LICENSE.md └── README.md /LICENSE.md: -------------------------------------------------------------------------------- 1 | Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## License 2 | 3 | Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 4 | 5 | ## Author 6 | 7 | Created by Jeff Leek: [http://jtleek.com/](http://jtleek.com/) 8 | 9 | 10 | ## Talks 11 | 12 | ## 2024 13 | 14 | * _Jeff_:[Building an oncology AI engine at the Fred Hutch and beyond](https://docs.google.com/presentation/d/1gnQSdqnMxr3YnKTlsXw43qLgjgA8ZeRDLz5XJJbJXeM/edit?usp=sharing) 15 | * _Jeff_:[(Bio)statistics in the AI age](https://docs.google.com/presentation/d/1yDs9mAf6MAdHFZAgfqpA3vDGaqyd_3gio3X252Fld6w/edit?usp=sharing) 16 | * _Jeff_:[Post-prediction inference](https://docs.google.com/presentation/d/15akv9xqWCCh4xdaDxjFHEecZcUJNlwolT_ALaQOcdxA/edit?usp=sharing) 17 | * _Jeff_:[Data to impact](https://docs.google.com/presentation/d/17DtLyxHCmpBCH8ylhyn_8-Bl17T_0HVvI7LPz8_w1bM/edit?usp=sharing) 18 | * _Jeff_:[Post-prediction inference](https://docs.google.com/presentation/d/1pAmPlnUqPuf1wsBTjWvHWXSkgKBqRdkBFuc6QxdnUN8/edit?usp=sharing) 19 | * _Jeff_:[AI in translational oncology](https://docs.google.com/presentation/d/1mg4cob2ebh7zpRPZGHgPHsHu2HzJS8xYMpg6JO4KFbU/edit?usp=sharing) 20 | * _Jeff_:[Inference with predicted data](https://docs.google.com/presentation/d/1-jWBWpf8JQT-YABo0arewDq9ptHNmS6YDTLGLwAHY1k/edit?usp=sharing) 21 | * _Jeff_:[Building the Fred Hutch Data Science Lab](https://docs.google.com/presentation/d/15SNb8XDITvlYCbK-HBDVneyEkdoDF_8hHk3T9yv5aJw/edit?usp=sharing) 22 | * _Jeff_:[Taking calculated career risks to impact the world through data science](https://docs.google.com/presentation/d/1K4vmgHlBTuCKamvbYi4UeZdMGweY52wRyo-UCaVkFwU/edit?usp=sharing) 23 | 24 | ## 2023 25 | * _Jeff_: [Studying gene expression at population scale with recount(Fred Hutch)](https://docs.google.com/presentation/d/16LHYHkr8OqcbOdMUSDum2_0lL4yZPZjh/edit?usp=sharing&ouid=101173740013479774353&rtpof=true&sd=true) 26 | * _Jeff_: [Studying gene expression at population scale with recount](https://docs.google.com/presentation/d/1wQxh9ZRn-hTebmuWkU1jiE6JN4oLmrTx/edit?usp=sharing&ouid=101173740013479774353&rtpof=true&sd=true) 27 | * _Jeff_: [Population scale transcriptomics for precision oncology (UW)](https://docs.google.com/presentation/d/1qZ2Inb3SeHvdpHnmiIdFpGUflJcmPBee/edit?usp=sharing&ouid=101173740013479774353&rtpof=true&sd=true) 28 | * _Jeff_: [Population scale transcriptomics for precision oncology (Cincinatti Children's)](https://docs.google.com/presentation/d/1Zuq0vopjmxhARn1vmZcUU1QbsQn8Typh/edit?usp=sharing&ouid=101173740013479774353&rtpof=true&sd=true) 29 | * _Jeff_: [Adventures in teaching data science big and small](https://docs.google.com/presentation/d/13zLvvgpd6uwy9My6dE9ww58np8xM2XdOY1W-uNYh90I/edit?usp=sharing) 30 | 31 | ### 2022 32 | 33 | * _Jeff_: [Population scale transcriptomics for precision oncology (FHCC)](https://docs.google.com/presentation/d/1sxwfP4ieBUSlvYc5WNL3I8w06J8rV6I3/edit?usp=sharing&ouid=101173740013479774353&rtpof=true&sd=true) 34 | * _Jeff_: [Post-prediction inference (UW)](https://docs.google.com/presentation/d/1vOaxombdaBdggtnPX1UVsAUSq6ueuwB6eE8HNZylqf4/edit?usp=sharing) 35 | * _Jeff_: [Post-prediction inference (Flatiron Research X)](https://docs.google.com/presentation/d/1QuEOxXoE9A55Fzt4ciBAVA99AEnRJn9jHbcKgtq_5U8/edit?usp=sharing) 36 | * _Jeff_: [Adventures in teaching big and small. From online Coursera courses to community based data science education](https://docs.google.com/presentation/d/1O5g1T7SjPMoIvvC1_FbaZU7vqZ_riqihXFd3Uebc_ZA/edit?usp=sharing) 37 | * _Jeff_: [Datatrail – Biostatisticians Building Inclusive Data Science Communities 38 | (UMich Social Good)](https://docs.google.com/presentation/d/1GfwTx3MCe32wNy6NDodMpDk5vJSLX1CqIo_E7ynTfq0/edit?usp=sharing) 39 | 40 | ### 2021 41 | 42 | * _Jeff_: [DataTrail - Biostatisticians building inclusive data science communities (Fred Hutch)](https://docs.google.com/presentation/d/16b2qsOiRMxQBqfqUWnIToQAhMwMvHuh82WODc38Oovc/edit?usp=sharing) 43 | * _Jeff_: [Post-prediction inference (TorBug)](https://docs.google.com/presentation/d/1P8duLvRdmJDbNdGyEHgQ98k2zsiZ7l7mQ0CrirwimHI/edit?usp=sharing) 44 | * _Jeff_: [What you can learn about human gene expression when making 70,000 RNA-seq samples easy to use (VATDSI) 45 | ](https://docs.google.com/presentation/d/1-M07fMf7fE4aLr_vGspFQnP26nxiWS7Z1jB0Emm7PLQ/edit?usp=sharing) 46 | 47 | ### 2020 48 | 49 | * _Jeff_: [The winding path to reproducibility in AI (AACR)](https://docs.google.com/presentation/d/16VP2Dkd3Q5LnZ9gc8814QpRF4r72ZgHg0O1HyXf89Yo/edit?usp=sharing) 50 | * _Jeff_: [Mutually intensive data science learning as an economic and public health intervention](https://docs.google.com/presentation/d/1XT0GTYLdDxn59VRF8kbWtcbNwfiEWB3RHnrcgxbvI-E/edit?usp=sharing) 51 | * _Jeff_: [Post-prediction inference](https://docs.google.com/presentation/d/1a85l3QOtnuO_1mjGnqEXnluk0jQXGuol_E0udQ9-fvk/edit?usp=sharing) 52 | * _Jeff_: [Mutually intensive data science learning as an economic and public health intervention](https://docs.google.com/presentation/d/17e8r1ZpjHmLQq49JTEV5t-wR2j-8hnOpAoxuk1_-VzU/edit?usp=sharing) 53 | * _Jeff_: [Mutually intensive data science learning as an economic and public health intervention ](https://docs.google.com/presentation/d/1siaFeo2ES6VKog3ksFF-5IUeuUbP4yUQUc0bK5JDnlQ/edit?usp=sharing) 54 | * _Jeff_: [Why you should care about statistics](https://docs.google.com/presentation/d/1VdEM9RIBKE1lkd590q3RXB0cbghjfOWhLUtcxxnb9vM/edit?usp=sharing) 55 | * _Jeff_: [The Johns Hopkins Data Science Lab Overview](https://docs.google.com/presentation/d/15hmde7rCTI6GKwydLchK4qgJws0uafbIoriRH_BvQfk/edit?usp=sharing) 56 | 57 | ### 2019 58 | 59 | * _Jeff_: [Using data science to create economic opportunities in East Baltimore](https://docs.google.com/presentation/d/1ZMrlruXg5yZJPEdKVt5wyMwG89k2e8_maPuFhQwf5u0/edit?usp=sharing) 60 | * _Jeff_: [Human data interaction (things we don't know)](https://docs.google.com/presentation/d/1_DdyJbITRwRI-iY2S6fL9EiPL28ViefHvh0lmyBh8hU/edit?usp=sharing) 61 | * _Jeff_: [(Genomic) Data Science Education as an Economic and Public Health Intervention](https://docs.google.com/presentation/d/1nBzGsFYLaYRYfxS0bu53CjYw6Gd4lEoJACdrVW6oBjQ/edit?usp=sharing) 62 | * _Jeff_: [Data Science Education as an Economic and Public Health Intervention—How (bio)Statisticians Can Lead Change in the World](https://docs.google.com/presentation/d/19EZ0cjULt8RKcEG1unsHL3bnV_zwzRq5Uyj9DLajQxM/edit?usp=sharing) 63 | * _Jeff_: [Data Science Education as an Economic and Public Health Intervention—How Biostatisticians Can Lead Change in the World](https://docs.google.com/presentation/d/1MG_7HmZ1tTsepuka3NILxoAwkb3hD8_y4zA2tbWBMbU/edit?usp=sharing) 64 | * _Jeff_: [Inference after prediction](https://docs.google.com/presentation/d/1KPwql_YeVXyUImd9ZL4w2IGUduaN6c4DEbVuLn5vif4/edit?usp=sharing) 65 | * _Jeff_: [The future of educational content development is plain text](https://docs.google.com/presentation/d/16z5tJAJvW5bqheGr3UgfIdaugohWBuIIImif7n6x7kI/edit?usp=sharing) 66 | * _Jeff_: [The relationship between statistics and trust in science](https://docs.google.com/presentation/d/1mWhuyCTFEJSzCqLQrRxgsdyi2h7NhIm8rSxDuOnAA5M/edit?usp=sharing) 67 | * _Jeff_ : [Medicine is a data science we should teach like it](https://docs.google.com/presentation/d/1Rpq0AvLVBw3-sIko8GTTWr25UnD3joEqnT1WTZVmwXI/edit?usp=sharing) 68 | * _Jeff_ : [Navigating the garden of forking paths -- multiple testing and p-hacking and pre-registration (oh my!)](https://docs.google.com/presentation/d/1HZLts6gBiTfBT09Zck7vlPAAb988gD_Ni45PCoBjUkQ/edit?usp=sharing) 69 | * _Jeff_ : [Data science education as a scalable public health intervention (Irvine)](https://docs.google.com/presentation/d/1kaNinoJ5zIYp_WetfflXiJ3c52jvSEhUBjISHgZMAcE/edit?usp=sharing) 70 | * _Jeff_: [Data science education as a scalable public health intervention (Chicago)](https://docs.google.com/presentation/d/1a4j7lHEDrLY8586Jk57VYrK8N43wfQlukCaVlEC9CTo/edit?usp=sharing) 71 | * _Jeff_: [Is most published research false? (a case study in reproducibility)](https://docs.google.com/presentation/d/1c7sGP9tav6OSE50nFotc-HlS0SLlvVxK_Lcu3b_LDvA/edit?usp=sharing) 72 | * _Jeff_: [Studying Human Gene Expression at Population Scale with the Recount Project](https://docs.google.com/presentation/d/1UdPYwoY4NaZkKdfFZfnOmDX2-W7qYb4pYZPwzFmbxRk/edit?usp=sharing) 73 | 74 | 75 | ### 2018 76 | 77 | * _Jeff_: [10 statistics tips (and why you should use them!)](https://docs.google.com/presentation/d/1VZ_TnmyvC98lwTx5ukZm88y2dcg0S1uOIz5V8kwWSYI/edit?usp=sharing) 78 | * _Jeff_: [Human-behavioral challenges in reproducibility & replicability (ReproZurich)](https://docs.google.com/presentation/d/1Z4knK4qz8zxMJvbk8melKkgq1qo38eqEJkJt5D37t0E/edit?usp=sharing) 79 | * _Jeff_: [Human data interaction - things we don't know (JSM 2018)](https://docs.google.com/presentation/d/1oCbf8NHpJSQAe6LoeD--wV-KbKbdGawrLHYJqwzfj_M/edit?usp=sharing) 80 | * _Jeff_: [Data science in (bio)stats departments (ASA Chairs)](https://docs.google.com/presentation/d/1Hayp7JQH7uy_X-GOq5vPoAR9Ver0xRJS5PrVqWb87u4/edit?usp=sharing) 81 | * _Jeff_: [Studying Human Gene Expression at Population Scale with the Recount Project (UCSD 2018)](https://docs.google.com/presentation/d/1eixophYVMrNM479mDrCm24wRKiCNh0Xi2T6FhaNX1lQ/edit?usp=sharing) 82 | * _Jeff_: [Improving the value of public genomic data with phenotype prediction (SAGES 2018)](https://docs.google.com/presentation/d/1iX1iNGvqqW2sWJd1a5BPEMCV1Z-cRd4Q_XIVSfWICoM/edit?usp=sharing) 83 | * _Jeff_: [Defining and implementing reproducibility and replicability (SCT2018)](https://docs.google.com/presentation/d/1lLgk7BEo65xSHldRoaX26zao7I2cJcXKyZIJxtNq27o/edit?usp=sharing) 84 | * _Jeff_: [The future of data science is plain text (eCOTs)](https://docs.google.com/presentation/d/13d_Pn3aOFjm0Rze9qo9K_8ZIwt4n9Hqv3yec-XAaRMI/edit?usp=sharing) 85 | * _Jeff_: [Predicting and using metadata (Yale)](https://docs.google.com/presentation/d/1QKDIGUKrO8tZkR355_Bg5MGA4fUvr3AdICPlXXg8XoI/edit?usp=sharing) 86 | * _Jeff_: [Predicting and using metadata (Toronto)](https://docs.google.com/presentation/d/1FgUZZU6pW91J7zH0OqrEgxfnV1Py_ZGL3ZKHfbOZskY/edit?usp=sharing) 87 | * _Jeff_: [Human behaviorial challenges in biomedical data science](https://docs.google.com/presentation/d/1uFxTgBXe55OmU55V_uV-AawCH3eiIkHP_Y00Kzyj0jg/edit?usp=sharing) 88 | * _Jeff_: [Human-data interaction (Washington)](https://docs.google.com/presentation/d/1nVAw7E-snu_bcCNhSlUuCP6eWYMxNBDJvsS_Ak4k0D0/edit?usp=sharing) 89 | * _Jeff_: [Is most published research really false? (Columbia)](https://docs.google.com/presentation/d/1S9VXkcMLZZ405rMQOaIz1OyNw-43Kt5hER4wcUS1H6M/edit?usp=sharing) 90 | 91 | ### 2017 92 | 93 | 94 | * _Jeff_: [The data science problem is humans and the solution is the internet](https://docs.google.com/presentation/d/1f2Kzwh0ObGo7TACIzCIa5GsI3UqF8Eez11RT3TdwypU/edit?usp=sharing) 95 | * _Jeff_: [Building a human gene expression resource (New York Genome Center)](https://docs.google.com/presentation/d/1_fNKQAHe3_ALBVUyRIZ83sRIsdq9O6ygnPTyrRvRXQI/edit?usp=sharing) 96 | * _Jeff_: [Is most published research false? (McGill)](https://docs.google.com/presentation/d/1hzdSDaPPSE9xUYZHhOVfQIRPPdwe0A9SdE7QDsK3bOA/edit?usp=sharing) 97 | * _Jeff_: [Coming to terms with data overload in science](https://docs.google.com/presentation/d/1diGUr8oHmJByBJy9eEvLBh3qIpUIjjy1P2TxasAWSHo/edit?usp=sharing), [pdf](https://github.com/jtleek/jtleek.github.io/files/1185814/jsm2017.pdf) 98 | * _Jeff_: [What can we (& you) learn about RNA from 70,000 (human) samples? (UCLA)](https://docs.google.com/presentation/d/1OGOVApkE72TqCWV0aMOfiwLzzZWoH8ZCprOWs8Pz1R0/edit?usp=sharing) 99 | * _Jeff_: [What can we (& you) learn about RNA from 70,000 (human) samples? (OHSU)](https://docs.google.com/presentation/d/1rAXyjdIvRBkRw93DinMUhfj9vs9yqfcEBctD4jO-Xgo/edit?usp=sharing) 100 | * _Jeff_: [What can we (& you) learn about RNA from 70,000 (human) samples?](https://docs.google.com/presentation/d/1mjMF1yDGgLQW4JNgiKO7XBY7I7j2laTq1kGYo3Q1rYw/edit?usp=sharing) 101 | * _Jeff_: [Data Science as a Science](https://docs.google.com/presentation/d/1qf4_78ArLmL6MWwchLm1HPMBft5jJfdEhpTk2UPecHo/edit?usp=sharing) 102 | * _Jeff_: [What can we learn about RNA from 70,000 (human) samples?](https://docs.google.com/presentation/d/1GBdWeHU5HI6Fqy9NDe_6RL2oDl5HjJdsmCHSBlAk0m4/edit?usp=sharing) 103 | * _Jeff_: [Is most published research really false?](https://docs.google.com/presentation/d/12SAKwzNs97DjcwTvIUi5husTf3EFlX_pfyxCKRjictE/edit?usp=sharing) 104 | 105 | ### 2016 106 | 107 | * _Jeff_: [Re-annotating the human transcriptome with recount](https://docs.google.com/presentation/d/1XCLfuCD1A0ODczmg4oKK5E3n-dwh6ohHjCYSj_doqbU/edit?usp=sharing) 108 | * _Jeff_: [Is the p-value really the problem?](https://docs.google.com/presentation/d/1nbaKvANCZkN8hbrd31R25WIfQszWFjGyiGeRaqHO1pI/edit?usp=sharing) 109 | * _Jeff_: [Data science as a science](http://www.slideshare.net/jtleek/data-science-as-a-science) 110 | 111 | 112 | ### 2015 113 | 114 | * _Jeff_: [JHU Data Science MOOCs - behind the scenes](http://www.slideshare.net/jtleek/jhu-data-science-moocs-behind-the-scenes) 115 | * _Jeff_: [Fixing the leaks in the pipeline from public genomics data to the clinic](http://www.slideshare.net/jtleek/fixing-the-leaks-in-the-pipeline-from-public-genomics-data-to-the-clinic) 116 | * _Jeff_: [Evidence based data analysis (NAS workshop on statistical reproducibility)](http://www.slideshare.net/jtleek/evidence-based-data-analysis) 117 | * _Jeff_: [We are all statisticians now (Rome Science Festival)](http://www.slideshare.net/jtleek/leek-romesf2015) 118 | * _Alyssa_: [High-resolution gene expression analysis (PhD thesis defense)](https://speakerdeck.com/alyssafrazee/high-resolution-gene-expression-analysis) 119 | * _Leo_: [Dissecting human brain development at high resolution using RNA-seq (ENAR 2015)](http://www.slideshare.net/lcolladotor/dissecting-human-brain-development-at-high-resolution-using-rnaseq) 120 | 121 | 122 | ### 2014 123 | 124 | 125 | * _Jeff_: [We are all statisticians now](https://speakerdeck.com/jtleek/we-are-all-statisticians-now) 126 | * _Jeff_: [Big data and reproducibility](https://speakerdeck.com/jtleek/big-data-and-reproducibility/) 127 | * _Alyssa_: [Adventures in Computational Biology](https://speakerdeck.com/alyssafrazee/adventures-in-computational-biology) 128 | * _Jeff_: [Data science education at JHSPH](http://www.slideshare.net/jtleek/education-37613273) 129 | * _Jeff_: [Statisticians and big data](http://www.slideshare.net/jtleek/big-data-and-statisticians) 130 | * _Alyssa_: [Engineering new tools for differential expression analysis](https://speakerdeck.com/alyssafrazee/differential-expression-analysis-tools) 131 | * _Jeff_: [10 things statistics taught us about big data](http://www.slideshare.net/jtleek/10-things-statistics-taught-us-about-big-data) 132 | * _Jeff_: [Genomics at JHU Biostats](http://www.slideshare.net/jtleek/flash-talk-about-johns-hopkins-genomics) 133 | * _Jeff_: [The world's largest data science program: The Johns Hopkins Data Science Specialization](http://www.slideshare.net/jtleek/the-largest-data-science-program-in-the-world-the-johns-hopkins-data-science-specialization) 134 | 135 | ### Old 136 | 137 | * _Jeff_: [JHU Job Talk (2009)](http://www.slideshare.net/jtleek/jhu-feb2009) 138 | --------------------------------------------------------------------------------