Project background:
Human embryonic development is a complex and mysterious process involving the differentiation and tissue formation of many cell types. single-cell sequencing (RNA-SEQ) is a technique capable of revealing gene expression differences and regulatory networks at the level of individual cells, providing new perspectives and tools for the study of human embryonic development. In recent years, using single-cell sequencing technology, researchers have constructed a gene expression map of the early stages of human embryo development (from the fertilized egg to the blastocyst stage) and identified some important genes and signaling pathways that play a role in cell differentiation and tissue formation. However, the regulatory network of gene expression in early human embryonic development remains unclear and requires further study.
Project Information: This project aims to analyze gene expression regulatory networks in the early stages of human embryo development (from fertilized egg to blastocyst stage), and explore the interactions between different cell types and the functions of transcription factors by using single-cell sequencing technology.

The following methods will be adopted in this project:
1. Obtain single-cell sequencing data in the early stage of human embryo development from a public database, and conduct quality control, normalization, batch correction and other pre-processing steps.
2. Cluster analysis, principal component analysis, t-SNE and other dimensionality reduction methods were used to identify and visualize single cell data.
3. Using differential expression analysis, enrichment analysis, co-expression network analysis and other methods to screen out genes with significant differences in different cell types, and analyze their functions and pathways.
4. Using methods such as prediction of transcription factor binding sites, inference of transcription factor activity, and reconstruction of transcription regulatory network, we identified transcription factors that play a key role in the early development of human embryos and analyzed their regulatory networks.
Project content:
The first stage: data acquisition and preprocessing. Single cell sequencing data from early human embryo development were downloaded from a public database and pre-processed using R language and Bioconductor package for quality control, normalization, batch correction and other steps to obtain a data matrix for subsequent analysis.
The second stage: cell type identification and visualization. R language and Seurat package were used for cluster analysis, principal component analysis, t-SNE and other dimensionality reduction methods to identify single cell data, and ggplot2 package was used for visualization to show the distribution of different cell types in two-dimensional or three-dimensional space.
The third stage: differential expression gene screening and functional analysis. Differential expression analysis was performed using R language and limma package to screen out genes with significant differences in different cell types, and enrichment analysis was performed using R language and clusterProfiler package to analyze the role of these genes in biological processes, molecular functions and pathways. At the same time, R language and WGCNA package were used for co-expression network analysis to construct gene co-expression networks of different cell types and identify key modules and genes in the networks.
The fourth stage: transcription factor identification and regulatory network analysis. R language and HOMER package were used to predict transcription factor binding sites to predict upstream transcription factors of differentially expressed genes, and R language and SCENIC package were used to infer transcription factor activity to infer transcription factors with different activities in different cell types. Finally, the transcription regulatory network was reconstructed using R language and igraph package to reconstruct the transcription regulatory network in the early stage of human embryonic development, and its topology and functional modules were analyzed.
Topic innovation:
1. This topic is a study of gene expression regulation network in early human embryonic development based on single-cell sequencing technology, which is a relatively advanced and popular research direction at present, and has high academic value and social significance.
2. This study adopted a variety of data analysis methods to reveal gene expression differences and regulatory mechanisms in the early stage of human embryo development from different perspectives and levels, providing a new perspective and tool for understanding the molecular basis of human embryo development.
3. This study identifies transcription factors and regulatory networks that play a key role in the early stage of human embryo development, providing new clues and candidate targets for revealing the regulatory logic of human embryo development and designing intervention strategies for human embryo development.