singha53-zz
commented
7 years ago Some comments:
1. The rationale is unclear to me: you state, "We will study the transcription factors (TFs) specifically expressed in one cell type (transcriptional signature) and the epigenomic features of different cells."
- do you want to associate TF gene expression in the parent hematopoietic stem cells with methylation of the differentiated cell-types? please clarify...
- how will you study the TF expression in one-cell-type (compare its expression profiles with samples from other cell-types? clarify)
- Also please state, the numbers of samples available for each cell-type(s), omic data, etc. Keep in mind depending on the number/size of the RNA-Seq fastq files, you may need access to a cluster in order to preprocess (QC, align, map, summarise to counts) RNA-Seq files.
- also state if previous studies have tried to address the question already. What is the knowledge gap your are trying to address?
2. The preliminary plan includes:
Using RNA-seq data to find signature genes and generate a list of essential TFs for the development of each cell type;
- what do you mean by signature? differentially expressed genes? biomarker panel? If you are only interested in TFs are you only going to look at a a priori list of TFs? (where will you obtain that list?)
Using methylome and ChIP-seq of histone marks to identify active/poised promoter and enhancer regions, and recognize the TF binding motif within these regions to infer the important transcriptional regulation during differentiation;
- how will you identify "active/poised promoter and enhancer regions" --> what does active mean (e.g. % change in methylation?) --> any statistical methodology/comparison you will carry out?
Correlating these promoter/enhancer regions from (2) with gene expression to verify the transcriptional regulation;
- state statistical methodology (e.g. linear model with specific parameterization to answer your specific question of interest).
Constructing a TF network for lineage differentiation using these datasets and known TF interactions from literature.
- which method will you use? which database will you retrieve these TF interactions from? What software will you use? libraries?
Remember to add a table stating the division of labour (e.g. which individuals are involved in the study design, obtaining data, preprocessing data, cleaning data, QC of data, exploratory data analysis, statistical analyses, writing etc).
Happy to discuss further at Wednesday's seminar. Cheers
@santina
santina
Team name: Bloodies
Project summary: Our project is interested in how hematopoietic stem cells, a rare stem cell population able to regenerate all erythroid, myeloid and lymphoid lineages in humans, make cell fate decisions during multiple-stage differentiation. We will obtain RNA-seq, DNA Methylome and ChIP-seq data from a European public resource (BLUEPRINT: http://dcc.blueprint-epigenome.eu/#/home). We will study the transcription factors (TFs) specifically expressed in one cell type (transcriptional signature) and the epigenomic features of different cells.
The preliminary plan includes: 1) Using RNA-seq data to find signature genes and generate a list of essential TFs for the development of each cell type; 2) Using methylome and ChIP-seq of histone marks to identify active/poised promoter and enhancer regions, and recognize the TF binding motif within these regions to infer the important transcriptional regulation during differentiation; 3) Correlating these promoter/enhancer regions from (2) with gene expression to verify the transcriptional regulation; 4) Constructing a TF network for lineage differentiation using these datasets and known TF interactions from literature. There will be comparisons and statistical analyses involved in each step.