Pinned Repositories
ChIP-seq
BIOE 582 ChIP-seq project for E. coli for identifying enriched regions through peak calling
CRISPR-JAMBOREE
2nd IGVF CRISPR-JAMBOREE
CRISPR_FG_JAMBOREE
Tasks and files for the CRISPR-FG scPERTURB-SEQ Pipeline
CS418_IDS
Practice exercises and projects done as part of the course CS 418-Introduction to Data Sciences
Facial-Recognition
Facial recognition on human and chimpanzee faces using the most traditional method of Eigenfaces
GGR-cwl
CWL tools and workflows for GGR
ggr-cwl-ipynb-gen
Jupyter notebook generator to download and execute the processing files for GGR related datasets
Microarrays-data-analysis
Repo includes scripts written in R for Data proprocessing, DE analysis and GSEA on microarrays
pipeline_perturbseq_like
Reddy_lab
RevathyVenukuttan's Repositories
RevathyVenukuttan/Microarrays-data-analysis
Repo includes scripts written in R for Data proprocessing, DE analysis and GSEA on microarrays
RevathyVenukuttan/ChIP-seq
BIOE 582 ChIP-seq project for E. coli for identifying enriched regions through peak calling
RevathyVenukuttan/CRISPR-JAMBOREE
2nd IGVF CRISPR-JAMBOREE
RevathyVenukuttan/CRISPR_FG_JAMBOREE
Tasks and files for the CRISPR-FG scPERTURB-SEQ Pipeline
RevathyVenukuttan/CS418_IDS
Practice exercises and projects done as part of the course CS 418-Introduction to Data Sciences
RevathyVenukuttan/Facial-Recognition
Facial recognition on human and chimpanzee faces using the most traditional method of Eigenfaces
RevathyVenukuttan/GGR-cwl
CWL tools and workflows for GGR
RevathyVenukuttan/ggr-cwl-ipynb-gen
Jupyter notebook generator to download and execute the processing files for GGR related datasets
RevathyVenukuttan/pipeline_perturbseq_like
RevathyVenukuttan/Reddy_lab
RevathyVenukuttan/RNA-seq
RNA-seq analysis on Pasilla knockdown in Drosophila to identify the differentially expressed genes
RevathyVenukuttan/RNA-Seq-for-Differential-Expression
RNA-seq analysis for differential gene expression
RevathyVenukuttan/Unsupervised-Machine-Learning
Unsupervised machine learning techniques (clustering) on EEG data to identify epileptic and non-epileptic seizures