Spring 2027

Statistical Methods for Molecular Biology

Graduate course covering statistical and computational methods for statistical genomics, including QC, design, clustering, network analysis, and GWAS for NGS studies.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Qiongshi Lu

Students were told that consistent attendance and completion of homework assignments would result in receiving an A grade.

What you’ll be able to do

  • Understand the statistical and computational background underlying many state-of-the-art techniques for the pre-processing and analysis of high-throughput genomics datasets

  • Identify the appropriateness and limitations of such methods in a variety of settings.

  • Discuss scientific problems and identify the statistical and computational aspects embedded in the processing and analysis of genomics datasets.

  • Become proficient in select software packages commonly used in analysis of next-generation sequencing data.

Source: UW Guide 1 UW Guide 2

Grade history

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average GPA
letter grades
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
BMI/STAT 877

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Prerequisite text tree
  • Graduate/professional standing

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist

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Meeting source records

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Student experience

the class

Past student reviews · Qiongshi Lu

Lectures relied on screenshots from papers, leading to inconsistent notations and a fast pace that prioritized moving forward over student understanding.

Recent recorded grades — Fall 2020: 4.00 GPA, 100.0% A/AB (n=7 letter grades); Spring 2022: 3.93 GPA, 95.2% A/AB (n=21 letter grades); Spring 2024: 3.93 GPA, 93.3% A/AB (n=15 letter grades).

difficulty & workload

Past student reviews · Qiongshi Lu

Students were told that consistent attendance and completion of homework assignments would result in receiving an A grade.

Past student reviews · Qiongshi Lu

One student reported that the instructor explicitly wanted them to succeed and communicated clear expectations for achieving top marks.

Topics

  • Statistical genomics for human and experimental populations
  • QC, experimental design, clustering, network analysis, and GWAS for NGS studies

Skills

  • Quality control, experimental design, clustering, network analysis, and GWAS methods for NGS studies
  • Understanding statistical and computational backgrounds for pre-processing and analyzing high-throughput genomics datasets
  • Proficiency in select software packages for next-generation sequencing data analysis

Grades

Latest available · Spring 2024— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
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Grades over time

Through Spring 2024

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

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Student reviews

Original comments behind the course and instructor summaries.

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Grade history

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "b750ef3ba66f0e1adb1c9ae0a0acf8be900d450107b2291b082f6862d2a08284",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}