Liulab Github

Hzau Liulab Github Liulab has 12 repositories available. follow their code on github. Our research focuses on algorithm development and integrative mining from high throughput data to understand gene regulation in cancer biology. we have developed a number of widely used algorithms for transcription factor motif finding, chip chip chip seq dnase seq crispr screen data analysis.

Buaa Liulab Github To support the uniform analysis of bulk rna sequencing data, we developed a rna seq immune analysis pipeline named rima that is available at github liulab dfci rima pipeline. Model based analysis of genome wide crispr cas9 knockout (mageck) is a computational tool to identify important genes from the recent genome scale crispr cas9 knockout screens technology. liulab dfci has 24 repositories available. follow their code on github. Maestro model based analyses of transcriptome and regulome (maestro) is a comprehensive open source computational workflow for integrative analysis of single cell rna seq (scrna seq) and atac seq (scatac seq) data from multiple platforms. This is the course material for stat115 215 bio bst282 at harvard university. we thank many colleagues in the community, who helped dr. liu in prepare the stat115 215 bio bst282 course over the years.

Liulab Github Maestro model based analyses of transcriptome and regulome (maestro) is a comprehensive open source computational workflow for integrative analysis of single cell rna seq (scrna seq) and atac seq (scatac seq) data from multiple platforms. This is the course material for stat115 215 bio bst282 at harvard university. we thank many colleagues in the community, who helped dr. liu in prepare the stat115 215 bio bst282 course over the years. Liulab has 8 repositories available. follow their code on github. This is the course material for stat115 215 bio bst282 at harvard university. all the videos in this course are organized under the 2021 stat115 playlist. we thank many colleagues in the community, who helped dr. liu in prepare the stat115 215 bio bst282 course over the years. Maestro combines several dozen tools and packages to create an integrative pipeline, which enables scrna seq and scatac seq analysis from raw sequencing data (fastq files) all the way through alignment, quality control, cell filtering, normalization, unsupervised clustering, differential expression and peak calling, celltype annotation and trans. Liulab has 15 repositories available. follow their code on github.