# PFinder: A computational tool to identify genomic regions affected by perturbation

> **NIH NIH F31** · HARVARD MEDICAL SCHOOL · 2020 · $18,466

## Abstract

ABSTRACT
At the core of many biological experiments is the goal of comprehensively answering the question: What are the
effects of a perturbation? Perturbations are any functional alteration in a biological system and their genome-
wide effects can be measured by innumerable sequencing technologies. Nascent transcription assays, like GRO-
seq, PRO-seq, NET-seq, and TT-seq, are emerging methods to measure the direct effect of a perturbation on
transcription. To better leverage genome-wide nascent RNA sequencing data to more fully understand the
effects of perturbations on nascent transcription, new computational methods for identifying regions differentially
affected by experimental and control conditions must be developed and applied. I propose to address this need
by developing PFinder, a computational tool capable of identifying the regions affected by a perturbation. I will
demonstrate its utility by analyzing NET-seq data from a reverse genetic screen in S. cerevisiae to provide insight
into the roles of transcription regulatory proteins, in terms of both location and scale of effect. This will create an
annotation of the yeast genome with the transcriptional consequences of knocking out each factor, lending new
insight into transcription regulation. I will next apply PFinder to other nascent RNA sequencing data collected
from several human cell types treated with small molecules to uncover their novel effects. The results from this
proposal will establish a method that can be applied to any nascent RNA sequencing data to identify loci affected
by a perturbation genome-wide and without a prior hypothesis. PFinder and the insights it provides will enable
more thorough exploitation of nascent RNA sequencing data, both previously published and yet to be generated.

## Key facts

- **NIH application ID:** 9877957
- **Project number:** 5F31HG010570-02
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Katherine Coyne Lachance
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $18,466
- **Award type:** 5
- **Project period:** 2019-09-01 → 2021-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9877957

## Citation

> US National Institutes of Health, RePORTER application 9877957, PFinder: A computational tool to identify genomic regions affected by perturbation (5F31HG010570-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9877957. Licensed CC0.

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