Applied Bioinformatics Core

The Applied Bioinformatics Core provides specialized computational and analytical support for biomedical research. WMC Logo

What We Do

The Applied Bioinformatics Core (ABC) is a central service group that specializes in providing data management and analysis support to large genomic centers and research groups. The objective of the core is to provide analytical capabilities to support and advance biomedical research.
We have ample expertise analyzing biological data from diverse types of experiments including, but not limited to, high-throughput genomic assays.
We have extensive experience in building standardized workflows as well as customized, in-depth analyses with emphasis on thorough quality control and statistical rigor.
We perform detailed computational analyses that are driven by specific biological questions defined by the investigators.
We provide extensive reports with publication-ready images as well as the analysis source code.
The example projects should give you an impression of the most commonly performed analyses - we are by no means limited to them and are happy to tackle new challenges. Please contact us at abc@med.cornell.edu for inquiries.

Transcriptomics

Single-cell RNA-seq | Spatial transcriptomics | CITE-seq | Differential gene expression analysis with bulk RNA-seq | General RNA biology assays such as CLIP-seq or PRO-seq

Example Projects:

  • Single-cell RNA-seq of in vitro differentiated embryonic stem cells
  • Transcriptome changes induced by deletion of a GTPase
  • Combined CITE-seq and TCR-seq for understanding T cell populations driving autoimmunity

Epigenetics

ChIP-seq | ATAC-seq | Reduced representation bisulfite sequencing (RRBS) or targeted methylation | Whole Genome Bisulfite sequencing

Example Projects:

  • Effects of cancer drugs on chromatin accessibility
  • Whole-genome bisulfite sequencing of neuronal cells
  • Identifying key genes of neuronal differentiation using CUT&TAG

Genomics

Variant calling and annotation | Evolution of viral sequences | Classifications of pathogens

Example Projects:

  • Identification & annotation of genomic variants in different mutants of a rodent parasite
  • Functional annotation of sequence variants in a gene possibly related to a bleeding phenotype

Functional Analyses

GO term enrichments | Gene set enrichments | Pathway Analyses | DNA motifs | Integration of diverse data sets

Example Projects:

  • Understanding cancer-induced transcriptome changes in blood cells
  • Characterizing the effects of inhibitors of chromatin-associated molecules for immune cell functions

Computational Pipelines

Large-scale automation of analysis pipeline | Distribution and management of large datasets | Shiny apps

Example Projects:

  • HIPAA-certified pipeline for the identification of genomic variants in tumor patient samples (for the Institute for Precision Medicine)
  • PubShare data portal for downloading and sharing genomic data
  • Interactive application for storing, visualizing, and analyzing proteomics data

Training and Consulting

Walk-in clinic | Hands-on workshops | Meetings for coding tips exchange

Walk-in Bioinformatics Clinics

Consulting and hands-on help with questions relating to performing bioinformatics tasks
Currently held online. Please email abc@med.cornell.edu for details.

Hands-on Workshops

Regularly held, intensive 12-hours-long courses open to members of the Tri-Institutional network

  • Introduction to R
  • Introduction to UNIX
  • Differential gene expression analysis using RNA-seq

Data Analysis & Bioinformatics User Group (d:bug)

Monthly meetings to foster exchange of coding tips and tricks – open to anyone

Selected Publications

  • Stevenson EM, Terry S, Copertino D, Leyre L, Danesh A, Weiler J, Ward AR, Khadka P, McNeil E, Bernard K, Miller IG, Ellsworth GB, Johnston CD, Finkelsztein EJ, Zumbo P, Betel D, Dündar F, Duncan MC, Lapointe HR, Speckmaier S, Moran-Garcia N, Papa MP, Nicholes S, Stover CJ, Lynch RM, Caskey M, Gaebler C, Chun TW, Bosque A, Wilkin TJ, Lee GQ, Brumme ZL, Jones RB. (2022) SARS CoV-2 mRNA vaccination exposes latent HIV to Nef-specific CD8+ T-cells. Nat Commun. Aug 19;13(1):4888.
  • Shakiba M, Zumbo P, Espinosa-Carrasco G, Menocal L, Dündar F, Carson SE, Bruno EM, Sanchez-Rivera FJ, Lowe SW, Camara S, Koche RP, Reuter VP, Socci ND, Whitlock B, Tamzalit F, Huse M, Hellmann MD, Wells DK, Defranoux NA, Betel D, Philip M, Schietinger A. (2022) TCR signal strength defines distinct mechanisms of T cell dysfunction and cancer evasion. J Exp Med. Feb 7;219(2):e20201966.
  • Gearty SV, Dündar F, Zumbo P, Espinosa-Carrasco G, Shakiba M, Sanchez-Rivera FJ, Socci ND, Trivedi P, Lowe SW, Lauer P, Mohibullah N, Viale A, DiLorenzo TP, Betel D, Schietinger A. (2021) An autoimmune stem-like CD8 T cell population drives type 1 diabetes. Nature. Nov 30.
  • Notaras M, Lodhi A, Dündar F, Collier P, Sayles NM, Tilgner H, Greening D, Colak D. (2021) Schizophrenia is defined by cell-specific neuropathology and multiple neurodevelopmental mechanisms in patient-derived cerebral organoids. Mol Psychiatry. Nov 17.
  • Ren Y, Huang SH, Macedo AB, Ward AR, Conce Alberto WD, Klevorn T, Leyre L, Copertino DC, Mota TM, Chan D, Truong R, Rohwetter T, Zumbo P, Dündar F, Betel D, Kovacs C, Benko E, Bosque A, Jones RB. (2021) Selective BCL-XL Antagonists Eliminate Infected Cells from a Primary Cell Model of HIV Latency but not from Ex Vivo Reservoirs. J Virol. Jul 12;95(15):e0242520.
  • Guttikonda SR, Sikkema L, Tchieu J, Saurat N, Walsh RM, Harschnitz O, Ciceri G, Sneeboer M, Mazutis L, Setty M, Zumbo P, Betel D, de Witte LD, Pe'er D, Studer L. (2021) Fully defined human pluripotent stem cell-derived microglia and tri-culture system model C3 production in Alzheimer's disease. Nat Neurosci. Mar;24(3):343-354. doi: 10.1038/s41593-020-00796-z. [Epub ahead of print]
  • Fassel H, Chen H, Ruisi M, Kumar N, DeSancho MT, Hajjar KA. (2021) Reduced Expression of Annexin A2 is Associated with Impaired Cell Surface Fibrinolysis and Venous Thromboembolism. Blood. Apr 22;137(16):2221-2230.
  • Palikuqi B, Nguyen DT, Li G, Schreiner R, Pellegata AF, Liu Y, Redmond D, Geng F, Lin Y, Gómez-Salinero JM, Yokoyama M, Zumbo P, Zhang T, Kunar B, Witherspoon M, Han T, Tedeschi AM, Scottoni F, Lipkin SM, Dow L, Elemento O, Xiang JZ, Shido K, Spence JR, Zhou QJ, Schwartz RE, De Coppi P, Rabbany SY, Rafii S. (2020) Adaptable haemodynamic endothelial cells for organogenesis and tumorigenesis. Nature. Sep;585(7825):426-432.
  • Au CC, Furness JB, Britt K, Oshchepkova S, Ladumor H, Soo KY, Callaghan B, Gerard C, Inghirami G, Mittal V, Wang Y, Huang XY, Spector JA, Andreopoulou E, Zumbo P, Betel D, Dow L, Brown KA. (2020) Three-dimensional growth of breast cancer cells potentiates the anti-tumor effects of unacylated ghrelin and AZP-531. Elife. Jul 15;9:e56913.
  • Odell SC, Taki F, Klein SL, Chen RJ, Levine OB, Skelly MJ, Nabila A, Brindley E, Gal Toth J, Dündar F, Sheridan CK, Fetcho RN, Alonso A, Liston C, Landau DA, Pleil KE, Toth M. (2020) Epigenomically Bistable Regions across Neuron-Specific Genes Govern Neuron Eligibility to a Coding Ensemble in the Hippocampus. Cell Rep. Jun 23;31(12):107789.
  • Scott AC, Dündar F, Zumbo P, Chandran SS, Klebanoff CA, Shakiba M, Trivedi P, Menocal L, Appleby H, Camara S, Zamarin D, Walther T, Snyder A, Femia MR, Comen EA, Wen HY, Hellmann MD, Anandasabapathy N, Liu Y, Altorki NK, Lauer P, Levy O, Glickman MS, Kaye J, Betel D, Philip M, Schietinger A. (2019) TOX is a critical regulator of tumour-specific T cell differentiation. Nature. 571, 270–274.
  • Li QV, Dixon G, Verma N, Rosen BP, Gordillo M, Luo R, Xu C, Wang Q, Soh CL, Yang D, Crespo M, Shukla A, Xiang Q, Dündar F, Zumbo P, Witkin M, Koche R, Betel D, Chen S, Massagué J, Garippa R, Evans T, Beer MA, Huangfu D. (2019) Genome-scale screens identify JNK-JUN signaling as a barrier for pluripotency exit and endoderm differentiation. Nat Genet. [Epub ahead of print]
  • Yamada M, Cai W, Martin LA, N'Tumba-Byn T, Seandel M. (2019) Functional robustness of adult spermatogonial stem cells after induction of hyperactive Hras. PLoS Genet. 3;15(5):e1008139.
  • Dupnik KM, Bean JM, Lee MH, Jean Juste MA, Skrabanek L, Rivera V, Vorkas CK, Pape JW, Fitzgerald DW, Glickman M. (2018) Blood transcriptomic markers of Mycobacterium tuberculosis load in sputum. Int J Tuberc Lung Dis. 22(8):950-958.
  • Wong KG, Ryan SD, Ramnarine K, Rosen SA, Mann SE, Kulick A, De Stanchina E, Müller FJ, Kacmarczyk TJ, Zhang C, Betel D, Tomishima MJ. (2017) CryoPause: A New Method to Immediately Initiate Experiments after Cryopreservation of Pluripotent Stem Cells. Stem Cell Reports., 9(1):355-365.
  • Chaudhary, N, Gonzalez, E, Chang, SH, Geng, F, Rafii, S, Altorki, NK, & McGraw, TE. (2016) Adenovirus Protein E4-ORF1 Activation of PI3 Kinase Reveals Differential Regulation of Downstream Effector Pathways in Adipocytes. Cell Reports, 17(12).
  • Oren, DA, Wei, Y, Skrabanek, L, Chow, BKC, Mommsen, T, & Mojsov, S. (2016) Structural mapping and functional characterization of zebrafish class B G-protein coupled receptor (GPCR) with dual ligand selectivity towards GLP-1 and glucagon. PLoS ONE, 11(12):e0167718.
  • Bayliss J, Mukherjee P, Lu C, Jain SU, Chung C, Martinez D, Sabari B, Margol AS, Panwalkar P, Parolia A, Pekmezci M, McEachin RC, Cieslik M, Tamrazi B, Garcia BA, La Rocca G, Santi M, Lewis PW, Hawkins C, Melnick A, David Allis C, Thompson CB, Chinnaiyan AM, Judkins AR, Venneti S. (2016) Lowered H3K27me3 and DNA hypomethylation define poorly prognostic pediatric posterior fossa ependymomas. Sci Transl Med., 8(366):366ra161.
  • Palermo LM, Uppal M, Skrabanek L, Zumbo P, Germer S, Toussaint NC, Rima BK, Huey D, Niewiesk S, Porotto M, Moscona A. (2016) Features of Circulating ParainfluenzaVirus Required for Growth in Human Airway. MBio. 7(2):e00235.
  • Webster AF, Zumbo P, Fostel J, Gandara J, Hester SD, Recio L, Williams A, WoodCE, Yauk CL, Mason CE. (2015) Mining the Archives: A Cross-Platform Analysis of Gene Expression Profiles in ArchivalFormalin-Fixed Paraffin-Embedded Tissues. Toxicol Sci. 148(2):460-72.

The Team

Doron Betel
Doron Betel
Core Director

Friederike Dündar
Friederike Dündar
Genomic Scientist

Thadeous Kacmarczyk
Thadeous Kacmarczyk
Bioinformatics Software Engineer

Piali Mukherjee
Piali Mukherjee
Computational Biology Associate

Lucy Skrabanek
Luce Skrabanek
Education and Outreach Coordinator

Paul Zumbo
Paul Zumbo
Senior Staff Associate of Computational Genomics

Computational Genomic Scientist Position

The Applied Bioinformatics Core (ABC) at Weill Cornell Medicine (WCM) in New York City is seeking a highly skilled computational biologist with a strong analytical background, driven to tackle the mysteries of biology with high-throughput data. We are looking for a bright and motivated person to join our team of experienced bioinformaticians.

The ABC is a well-established central service group located within the thriving Tri-I research environment created by Weill Cornell Medicine, Memorial Sloan Kettering Cancer Center, and Rockefeller University. We provide analytical capabilities to support the cutting-edge biomedical research at WCM spanning virtually all areas of basic and biomedical science. Faculty and staff at this core facility have extensive expertise analyzing biological data from diverse types of high-throughput experiments, building standardized workflows as well as custom-tailored analyses with an emphasis on thorough quality control and statistical rigor. .

As a computational genomic scientist at the ABC, you will perform in-depth analyses of high-throughput data (single-cell and bulk RNA-seq, CITE-seq, ATAC-seq, ChIPseq/CUT&TAG, WGBS, etc.) to address a multitude of biological or clinical questions at the forefront of research across the WCM community. Central to this position is the ability to quickly develop a deep understanding of the underlying biology that each project addresses and of the scope and limitations of the individual experimental methods that are used. We are looking for candidates with deep knowledge of genomics, cell biology, and experimental protocols related to DNA sequencing and/or other ‘omics data types who are passionate about science and data analysis.

Qualifications we are looking for:

  • Master’s degree or PHD (preferred) in Statistical/Computational Genomics or Bioinformatics, with a strong background in the biological sciences.
  • Expertise in Unix environment, shell scripting, high performance computing, cloud and cluster environments, and version control with git.
  • Intimate knowledge of common high-throughput sequencing analysis tools such as short-read/sequence aligners (STAR, salmon, BWA etc.), single-cell analysis packages (Bioconductor, scanpy, Seurat etc.), visualization approaches, and functional annotation of sequencing data.
  • Strong programming skills in at least one of Python, R, Julia; or compiled languages such as C/C++, Rust, and JAVA.
  • Critical and creative thinking, detail-oriented work, enthusiasm to work on team projects, effective communication and presentation skills, never-ending curiosity, problem solving and passion for educating fellow staff, students and faculty about bioinformatics principles.
You will:
  • Be responsible for designing and carrying out bioinformatics and biostatistical analyses of next generation sequencing (NGS) datasets from a variety of platforms, including Illumina and 10X Genomics. This includes a strong focus on quality control and critical assessment of the experimental design as well as normalization, clustering, visualization, cellular annotation (for single-cell assays) and additional downstream analyses.
  • Collaborate with cross-disciplinary teams of WCM faculty, clinicians, trainees, and technicians from a variety of labs and centers, advising them on experimental design, data handling and analysis practices for a variety of experimental approaches, including transcriptomics, genomics and epigenomics methods;
  • Critically review, analyze, summarize, and communicate results as well as limitations of analyses to research faculty, staff, and clinical collaborators.
  • Prepare results for publications, work with collaborators in writing publications and optimizing visualizations.
  • Write robust code that is rigorously documented and liberally commented that that can easily be shared via code repositories.
  • Organize data in a systematic, resource-conscious way. Curate metadata and upload data sets to public repositories.
  • Actively participate in identifying, evaluating, and benchmarking new computational tools and methodologies that will meet the scientific goals of the ABC’s constituents;
  • Educate faculty and lab members in contemporary bioinformatics methods and best practices via small group training and one-on-one consulting.
This position combines the best aspects of industry and academia; it is ideal for PhD graduates looking to work in a thriving and stimulating research environment on cutting-edge medical and clinical research projects, directly impacting manifold research efforts. The focus of our work is to understand the data at hand and how it relates to the initial research question. If you enjoy detail-oriented data exploration, hypothesis testing, writing robust code, and contributing to a wide range of research projects without the pressure of having to publish papers or apply for grants, then this job is for you!

For recently published projects, check out GitHub page.

To apply for this position, please email your CV in PDF format only along with a short cover letter to abc@med.cornell.edu

Get in touch