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dotears: Scalable, consistent DAG estimation using observational and interventional data

Published: May 08, 2024

I presented at the NIHGRI conference in both 2023 and 2024 about dotears, which learns causal gene regulatory networks from Perturb-seq data. The relevant paper is here. This was as part of the UCLA Genomic Analysis and Interpretation Training Grant (T-32).

keju: powerful and accurate inference in Massively Parallel Reporter Assays

Published: March 24, 2026

I will be at Probgen 2026! Please say hi there.

dotears: Scalable and consistent directed acyclic graph estimation using observational and interventional data

Published in iScience, 2025

We learned causal gene regulatory networks using Perturb-seq data.

Recommended citation: Albert Xue, Jingyou Rao, Sriram Sankararaman, and Harold Pimentel (2025). "dotears: Scalable and consistent directed acyclic graph estimation using observational and interventional data." iScience, Volume 28, Issue 2, 111673. doi.org/10.1016/j.isci.2024.111673.
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Multiplexed Perturbation Enables Scalable Pooled Screens

Published in biorxiv, 2025

We see how cells react to multiple CRISPR perturbations.

Recommended citation: Stefan Oberlin, Neil Tay, Albert Xue, Harold Pimentel, and Michael T McManus (2025). "Multiplexed Perturbation Enables Scalable Pooled Screens." biorxiv.
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A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis

Published in Nature Genetics, 2025

We learn marginal epistasis in the UK Biobank.

Recommended citation: Boyang Fu, Ali Pazokitoroudi, Zuozheng Shi, Asha Kar, Albert Xue, Akarsh Anand, Prateek Anand, Zhengtong Liu, Richard Border, Päivi Pajukanta, Noah Zaitlen, and Sriram Sankararaman (2025). "A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis." Nature Genetics.
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keju: powerful and accurate inference in Massively Parallel Reporter Assays

Published in biorxiv, 2026

We build a better statistical tool for MPRAs.

Recommended citation: Albert Xue, Adam M Zahm, Justin English, Sriram Sankararaman, and Harold Pimentel (2026). "keju: powerful and accurate inference in Massively Parallel Reporter Assays." biorxiv.
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dotears: Causal structure learning using interventional data

Published: November 10, 2022

I gave a talk at the Biological Data Science CSHL conference about dotears, which learns causal gene regulatory networks from Perturb-seq data. The relevant paper is here.

CM 121 - Introduction to Bioinformatics

Undergraduate course, UCLA, Computer Science, 2023

I TAed CM 121 - Introduction to Bioinformatics for Harold, along with two other TAs. Topics included ranged from basic statistics topics like Maximum Likelihood, to RNA-seq normalization, to pseudoalignment, to dimension reduction and PCA. My responsibilities included writing (1/3 of the) lecture notes for discussion, giving discussion, grading, and responding to Piazza posts. If you’re curious, you can view my discussion notes here, here, and here.