# CSHL Statistical Methods for Functional Genomics Course

> **NIH NIH R25** · COLD SPRING HARBOR LABORATORY · 2021 · $92,149

## Abstract

PROJECT SUMMARY/ABSTRACT
The proposed Cold Spring Harbor Laboratory (CSHL) summer course on Statistical Methods for
Functional Genomics is to be held annually in 2021-2024. The primary objective of the course is to build
competence in statistical methods for analyzing high‐throughput data in genomics and molecular biology.
Over the past two decades, high‐throughput assays have become pervasive in biological research due to
both rapid technological advances and decreases in overall cost. Many standard genomic measures such
as methylation, copy-number variation, and chromatin immunoprecipitation have been adapted in recent
years to high-throughput formats, and this has produced an explosion of genome-scale data from multiple
organisms. Investigators are now needed who have robust training in relevant statistical methods for
analyzing such data. CSHL proposes to meet the need for this specialized, interdisciplinary training by
continuing to offer an advanced two-week course each summer entitled Statistical Methods for Functional
Genomics. This course will provide intensive, hands-on training that will prepare participants to initiate
analyses of large and complex biological data sets. In addition, the curriculum will address issues
common to all high-throughput technologies, such as identifying and compensating for systematic errors,
statistical significance on a genome-wide scale, and incorporating bioinformatics data into statistical
procedures. In-class exercises and demonstrations will be done using the R environment for statistical
computing as well as Bioconductor, an open‐source project in R for use in bioinformatics research. The
course instructors will be established researchers who are fully active in and have made significant
contributions to the analysis of complex biological data sets, and the instructors will be supplemented by
a series of invited speakers who will present current research in their fields of expertise to illustrate
principles taught in the course. The course will train approximately 24 students per year, ranging from
advanced graduate students to senior investigators. Applications are anticipated from scientists with a
variety of scientific backgrounds, including molecular evolution, development, neuroscience, cancer,
plant biology, and immunology. As with other CSHL postgraduate courses, the overarching goal of
Statistical Methods for Functional Genomics is to provide residential training in advanced methodologies
that participants can apply immediately to their own research.

## Key facts

- **NIH application ID:** 10088972
- **Project number:** 1R25HG011448-01
- **Recipient organization:** COLD SPRING HARBOR LABORATORY
- **Principal Investigator:** Charla A Lambert
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $92,149
- **Award type:** 1
- **Project period:** 2021-09-07 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10088972

## Citation

> US National Institutes of Health, RePORTER application 10088972, CSHL Statistical Methods for Functional Genomics Course (1R25HG011448-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10088972. Licensed CC0.

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