日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace

利用 Lilace 对基于 FACS 的深度突变扫描数据进行精确的变异效应估计

Freudenberg, Jerome; Rao, Jingyou; Howard, Matthew K; Macdonald, Christian; Greenwald, Noah F; Coyote-Maestas, Willow; Pimentel, Harold

Rosace-AA: enhancing interpretation of deep mutational scanning data with amino acid substitution and position-specific insights

Rosace-AA:利用氨基酸替换和位置特异性见解增强对深度突变扫描数据的解读

Rao, Jingyou; Wang, Mingsen; Howard, Matthew K; Macdonald, Christian; Fraser, James S; Coyote-Maestas, Willow; Pimentel, Harold

Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning.

通过深度突变扫描绘制MET受体酪氨酸激酶的激酶结构域抗性机制图谱

Estevam Gabriella O, Linossi Edmond, Rao Jingyou, Macdonald Christian B, Ravikumar Ashraya, Chrispens Karson M, Capra John A, Coyote-Maestas Willow, Pimentel Harold, Collisson Eric A, Jura Natalia, Fraser James S

Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace

利用 Lilace 对基于 FACS 的深度突变扫描数据进行精确的变异效应估计

Freudenberg, Jerome; Rao, Jingyou; Howard, Matthew K; Macdonald, Christian; Greenwald, Noah F; Coyote-Maestas, Willow; Pimentel, Harold

Cosmos: A Position-Resolution Causal Model for Direct and Indirect Effects in Protein Functions

Cosmos:一种用于研究蛋白质功能中直接和间接效应的位置分辨率因果模型

Rao, Jingyou; Wang, Mingsen; Howard, Matthew; Coyote-Maestas, Willow; Pimentel, Harold

Cell villages and Dirichlet modeling map human cell fitness genetics

细胞村落和狄利克雷模型绘制人类细胞适应性遗传图谱

Hanson, Chloe; Derebenskiy, Tim; Vega, Ana Rodriguez; Kamte, Yashika S; Fox, Rachel G; Lambing, Hannah; Allard, Patrick; Pimentel, Harold; Wells, Michael F

Rosace: a robust deep mutational scanning analysis framework employing position and mean-variance shrinkage

Rosace:一种采用位置和均值-方差收缩的稳健深度突变扫描分析框架

Rao, Jingyou; Xin, Ruiqi; Macdonald, Christian; Howard, Matthew K; Estevam, Gabriella O; Yee, Sook Wah; Wang, Mingsen; Fraser, James S; Coyote-Maestas, Willow; Pimentel, Harold

Accounting for isoform expression increases power to identify genetic regulation of gene expression

考虑亚型表达可以提高识别基因表达遗传调控的能力。

LaPierre, Nathan; Pimentel, Harold

kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq

kallisto、bustools 和 kb-python 用于量化批量、单细胞和单核 RNA 测序数据。

Sullivan, Delaney K; Min, Kyung Hoi Joseph; Hjörleifsson, Kristján Eldjárn; Luebbert, Laura; Holley, Guillaume; Moses, Lambda; Gustafsson, Johan; Bray, Nicolas L; Pimentel, Harold; Booeshaghi, A Sina; Melsted, Páll; Pachter, Lior

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits

基因互作导致基因表达和复杂性状的因果变异效应大小存在异质性。

Patel, Roshni A; Musharoff, Shaila A; Spence, Jeffrey P; Pimentel, Harold; Tcheandjieu, Catherine; Mostafavi, Hakhamanesh; Sinnott-Armstrong, Nasa; Clarke, Shoa L; Smith, Courtney J; Durda, Peter P; Taylor, Kent D; Tracy, Russell; Liu, Yongmei; Johnson, W Craig; Aguet, Francois; Ardlie, Kristin G; Gabriel, Stacey; Smith, Josh; Nickerson, Deborah A; Rich, Stephen S; Rotter, Jerome I; Tsao, Philip S; Assimes, Themistocles L; Pritchard, Jonathan K