Our lab is interested in aneuploidy, or the incorrect number of whole chromosomes and chromosome arms. A challenge in this area of research is that karyotypes require a large number of proliferating cells for analysis. To address this, our lab and collaborators developed new algorithms to identify aneuploidy alterations from DNA sequencing data. Here, the project goal is to implement these algorithms at Columbia, and subsequently to apply these analysis methods to samples generated in the lab and patient samples. Building on this, the DSI student may also develop new algorithms for use with single-cell sequencing data and RNA sequencing data. Experience in one or more of the following is a must: UNIX, R, and python. The DSI student will be mentored by Dr. Alison Taylor, and he/she will also work closely with all lab members.

This project is eligible for a matching fund stipend from the Data Science Institute. This not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Alison Taylor
  • Department/School: Pathology and Cell Biology/CUIMC
  • Location: ICRC 3rd floor
  • The goal of the Taylor lab is to understand the role of aneuploidy, whole chromosome or chromosome arm imbalance, in the development of cancer. Using functional genomics, genome engineering methods, and analysis of patient genomic data, we study the effects of aneuploidy on signaling and cell fate.

Project Timeline

  • Earliest starting date: 10/1/2020
  • End date: 12/3/2020
  • Number of hours per week of research expected during Fall 2020: ~9

Candidate requirements

  • Skill sets: Experience in command line/UNIX, R, and/or python
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes