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simplify the title of lectures
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ypp committed Feb 18, 2024
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92 changes: 46 additions & 46 deletions course-admin/schedule_2024.csv
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course,lect,dow,month,day,week,lecture_num,raw_notes,instructor
STAT540-Seminar,seminar-1,Tue,January,9,1,1,"Introduction to version control, Git, GitHub", Ishika
STAT540-Seminar,seminar-2a,Tue,January,16,2,2,"Introduction to Markdown, Knitr", Ishika
STAT540-Seminar,seminar-2b,Tue,January,16,2,2,R graphics -- Intro to ggplot2, Ishika
STAT540-Seminar,seminar-3,Tue,January,23,3,3,Probability and simulations, Ishika
STAT540-Seminar,seminar-4,Tue,January,30,4,4,Reading in data and wrangling, Asfar
STAT540-Seminar,seminar-5,Tue,February,6,5,5,"Two group testing, fitting and interpreting linear models", Asfar
STAT540-Seminar,seminar-6,Tue,February,13,6,6,RNA-seq: from beginning to end -- BAM to count data, Ishika
STAT540-Seminar,No Seminar,Tue,February,20,7,NA,No seminar (reading break),
STAT540-Seminar,seminar-7,Tue,February,27,8,7,Methylation microarray analysis, Asfar
STAT540-Seminar,No Seminar,Tue,March,5,9,NA,No seminar,
STAT540-Seminar,seminar-8,Tue,March,12,10,8,Gene set enrichment analysis, Asfar
STAT540-Seminar,seminar-9,Tue,March,19,11,9,Unsupervised learning - clustering and dimension reduction, Asfar
STAT540-Seminar,seminar-10,Tue,March,26,12,10,"Supervised learning, cross-validation, variable selection", Ishika
STAT540-Seminar,seminar-11,Tue,April,2,13,11,eQTL analysis, Ishika
STAT540-Seminar,No Seminar,Tue,April,9,14,NA,No seminar,
,,,,,,,,
,,,,,,,,
,,dow,month,day,week,,,
STAT540,lecture-1,Tue,January,9,1,1,Course intro; Molecular biology primer,Keegan
STAT540,lecture-2,Thu,January,11,1,2,"High-dimensional biology intro: RNA, DNA, methylation, ChIP-Seq",Keegan
STAT540,lecture-3,Tue,January,16,2,3,Exploratory data analysis,Keegan
STAT540,lecture-4,Thu,January,18,2,4,Statistics & probability primer,Keegan
STAT540,lecture-5,Tue,January,23,3,5,Statistical inference: two groups,Keegan
STAT540,lecture-6,Thu,January,25,3,6,Statistical inference: linear regression & ANOVA,Keegan
STAT540,Presentations,Tue,January,30,4,NA,Project lightning talk,
STAT540,lecture-7,Thu,February,1,4,7,Statistical inference: multiple linear regression,Keegan
STAT540,lecture-8,Tue,February,6,5,8,Statistical inference: continuous model & limma,Keegan
STAT540,lecture-9,Thu,February,8,5,9,Statistical inference: multiple testing,Keegan
STAT540,lecture-10,Tue,February,13,6,10,Application of statistical inference to RNA-seq,Yongjin
STAT540,lecture-11,Thu,February,15,6,11,Application of statistical inference to epigenetics,Yongjin
STAT540,break,Tue,February,20,7,NA,Reading break (no class),
STAT540,break,Thu,February,22,7,NA,Reading break (no class),
STAT540,lecture-12,Tue,February,27,8,12,Gene set enrichment; confounding and batch effects,Keegan
STAT540,lecture-13,Thu,February,29,8,13,Supervised learning (univariate): GWAS and eQTL,Yongjin
STAT540,lecture-14,Tue,March,5,9,14,Supervised learning (multivariate): polygenic risk prediction,Yongjin
STAT540,lecture-15,Thu,March,7,9,15,Supervised learning (advanced): regulatory genomics and deep learning,Yongjin
STAT540,lecture-16,Tue,March,12,10,16,Sparse data analysis: technology and batch correction,Yongjin
STAT540,lecture-17,Thu,March,14,10,17,Classical unsupervised learning methods with applications in scRNA and pop gen,Yongjin
STAT540,lecture-18,Tue,March,19,11,18,Unsupervised embedding methods with applications in high-dimensional space,Yongjin
STAT540,lecture-19,Thu,March,21,11,19,"Classical clustering analysis: hierarchical agglomerative methods, k-means (EM)",Yongjin
STAT540,lecture-20,Tue,March,26,12,20,Spatial Transcriptomics: deconvolution and statistical alignment,Yongjin
STAT540,lecture-21,Thu,March,28,12,21,Multiomics data integration,Yongjin
STAT540,Presentations,Tue,April,2,13,NA,Final Project Presentations,
STAT540,Presentations,Thu,April,4,13,NA,Final Project Presentations,
STAT540,Presentations,Tue,April,9,14,NA,Final Project Presentations,
course,lect,dow,month,day,week,lecture_num,raw_notes,instructor
STAT540-Seminar,seminar-1,Tue,January,9,1,1,"Introduction to version control, Git, GitHub", Ishika
STAT540-Seminar,seminar-2a,Tue,January,16,2,2,"Introduction to Markdown, Knitr", Ishika
STAT540-Seminar,seminar-2b,Tue,January,16,2,2,R graphics -- Intro to ggplot2, Ishika
STAT540-Seminar,seminar-3,Tue,January,23,3,3,Probability and simulations, Ishika
STAT540-Seminar,seminar-4,Tue,January,30,4,4,Reading in data and wrangling, Asfar
STAT540-Seminar,seminar-5,Tue,February,6,5,5,"Two group testing, fitting and interpreting linear models", Asfar
STAT540-Seminar,seminar-6,Tue,February,13,6,6,RNA-seq: from beginning to end -- BAM to count data, Ishika
STAT540-Seminar,No Seminar,Tue,February,20,7,NA,No seminar (reading break),
STAT540-Seminar,seminar-7,Tue,February,27,8,7,Methylation microarray analysis, Asfar
STAT540-Seminar,No Seminar,Tue,March,5,9,NA,No seminar,
STAT540-Seminar,seminar-8,Tue,March,12,10,8,Gene set enrichment analysis, Asfar
STAT540-Seminar,seminar-9,Tue,March,19,11,9,Unsupervised learning - clustering and dimension reduction, Asfar
STAT540-Seminar,seminar-10,Tue,March,26,12,10,"Supervised learning, cross-validation, variable selection", Ishika
STAT540-Seminar,seminar-11,Tue,April,2,13,11,eQTL analysis, Ishika
STAT540-Seminar,No Seminar,Tue,April,9,14,NA,No seminar,
,,,,,,,,
,,,,,,,,
,,dow,month,day,week,,,
STAT540,lecture-1,Tue,January,9,1,1,Course intro; Molecular biology primer,Keegan
STAT540,lecture-2,Thu,January,11,1,2,"High-dimensional biology intro: RNA, DNA, methylation, ChIP-Seq",Keegan
STAT540,lecture-3,Tue,January,16,2,3,Exploratory data analysis,Keegan
STAT540,lecture-4,Thu,January,18,2,4,Statistics & probability primer,Keegan
STAT540,lecture-5,Tue,January,23,3,5,Statistical inference: two groups,Keegan
STAT540,lecture-6,Thu,January,25,3,6,Statistical inference: linear regression & ANOVA,Keegan
STAT540,Presentations,Tue,January,30,4,NA,Project lightning talk,
STAT540,lecture-7,Thu,February,1,4,7,Statistical inference: multiple linear regression,Keegan
STAT540,lecture-8,Tue,February,6,5,8,Statistical inference: continuous model & limma,Keegan
STAT540,lecture-9,Thu,February,8,5,9,Statistical inference: multiple testing,Keegan
STAT540,lecture-10,Tue,February,13,6,10,Application of statistical inference to RNA-seq,Yongjin
STAT540,lecture-11,Thu,February,15,6,11,Application of statistical inference to epigenetics,Yongjin
STAT540,break,Tue,February,20,7,NA,Reading break (no class),
STAT540,break,Thu,February,22,7,NA,Reading break (no class),
STAT540,lecture-12,Tue,February,27,8,12,Gene set enrichment; confounding and batch effects,Keegan
STAT540,lecture-13,Thu,February,29,8,13,"Supervised learning: GWAS and eQTL",Yongjin
STAT540,lecture-14,Tue,March,5,9,14,"Supervised learning: polygenic risk prediction",Yongjin
STAT540,lecture-15,Thu,March,7,9,15,"Supervised learning: post-GWAS & causal inference",Yongjin
STAT540,lecture-16,Tue,March,12,10,16,"Single-cell data analysis: technology and data normalization",Yongjin
STAT540,lecture-17,Thu,March,14,10,17,"Unsupervised learning: application of latent factor models to scRNA-seq",Yongjin
STAT540,lecture-18,Tue,March,19,11,18,"Unsupervised learning: recent approaches",Yongjin
STAT540,lecture-19,Thu,March,21,11,19,"Model-based analysis: statistical learning methods in genomics",Yongjin
STAT540,lecture-20,Tue,March,26,12,20,"Spatial Transcriptomics",Yongjin
STAT540,lecture-21,Thu,March,28,12,21,"Multiomics data integration",Yongjin
STAT540,Presentations,Tue,April,2,13,NA,Final Project Presentations,
STAT540,Presentations,Thu,April,4,13,NA,Final Project Presentations,
STAT540,Presentations,Tue,April,9,14,NA,Final Project Presentations,
STAT540,Presentations,Thu,April,11,14,NA,Final Project Presentations,
18 changes: 9 additions & 9 deletions lectures.html
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<style type="text/css">code{white-space: pre;}</style>
<style type="text/css" data-origin="pandoc">
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pre > code.sourceCode > span { line-height: 1.25; }
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code.sourceCode > span { color: inherit; text-decoration: inherit; }
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<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 13: Supervised learning (univariate): GWAS and eQTL
Lecture 13: Supervised learning: GWAS and eQTL
</td>
<td style="text-align:left;">
Yongjin
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<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 14: Supervised learning (multivariate): polygenic risk prediction
Lecture 14: Supervised learning: polygenic risk prediction
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2797,7 +2797,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 15: Supervised learning (advanced): regulatory genomics and deep learning
Lecture 15: Supervised learning: post-GWAS &amp; causal inference
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2810,7 +2810,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 16: Sparse data analysis: technology and batch correction
Lecture 16: Single-cell data analysis: technology and data normalization
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2823,7 +2823,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 17: Classical unsupervised learning methods with applications in scRNA and pop gen
Lecture 17: Unsupervised learning: application of latent factor models to scRNA-seq
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2836,7 +2836,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 18: Unsupervised embedding methods with applications in high-dimensional space
Lecture 18: Unsupervised learning: recent approaches
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2849,7 +2849,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 19: Classical clustering analysis: hierarchical agglomerative methods, k-means (EM)
Lecture 19: Model-based analysis: statistical learning methods in genomics
</td>
<td style="text-align:left;">
Yongjin
Expand All @@ -2862,7 +2862,7 @@ <h3 id="class-meetings-and-schedule">Class meetings and schedule</h3>
<td style="text-align:left;">
</td>
<td style="text-align:left;">
Lecture 20: Spatial Transcriptomics: deconvolution and statistical alignment
Lecture 20: Spatial Transcriptomics
</td>
<td style="text-align:left;">
Yongjin
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