Hey Everyone,
I hope you all are doing good. I am interested in analyzing microarray data of tumor gene expression. I want to identify the differentially expressed gene among wildtype VS Knockout. And to check their role, I used the AltAnalyze tool for normalization, heatmap, clustering and pathway study. Is anyone who familiar with this tool and its reliability or suggest me good and reliable tool license free. Can someone recommend me good article/material, How to dig out the meaningful information/hypothesis from microarray data results? I am a beginner in this field, I will be highly obliged for your valuable suggestions. I will be waiting for your answers. Thank you.
0 answers
No answers yet.
Log in to answer this question.
-
News: Course - Introduction to CRISPR for Ecology and Evolution Studies
written by Physalia-courses
-
Tutorial: Gene Set Enrichment Analysis
written by Hamid Ghaedi
-
Mapping expression profiles from microarray control set, to a collection of publicly available RNAs…
written by becton •
-
How to get Gene symbols from feature number?
written by Muhammad Haseeb •
-
News: Population genomics: here is the interview to our instructors Dr. Martin Taylor and Dr. Lewis…
written by Physalia-courses
-
Job: Bioinformatics Research Consultant needed for constructing TFBS and regulatory networks from t…
written by tfhahn •
-
Identifying differentially expressed genes from Wild type and Knockout data
written by Muhammad Haseeb •
-
Beginner In MicroArray Data Analysis
written by Muhammad Haseeb •
-
Help with finding tutors for GO enrichment analysis, R, Cytoscape, Python, Linux, Perl, Octave and/…
written by david.ballester •
-
Do You Have Source Codes / Snippets To Share?
written by Radhouane Aniba
I'm not familiar with the software you mentioned, but Bioconductor/R tools might be useful, see following links to get started:
Analysing Microarray Data In Bioconductor
Using Bioconductor for Microarray Analysis
Thank you very much for providing the link.
Regards,
AltAnalyze will produce a set of files in the folder GO-Elite under the folders upregulated, downregulated and regulated with pathway and ontology enrichment analyses that indicate likely regulated biologically relevant terms. The pruned results file will indicate these results and associated genes. In the folder ExpressionOutput you find the file with the prefix DATASET to sort and filter for the most significantly differentially expressed genes. I recommend filtering based on the adjusted p-value column which outputs an FDR adjusted empirical Bayes moderated t-test similar to limma in R. Note there are extensive gene and pathway annotations in this file. These and nearly all other results (colored pathways, heatmaps, networks, QC, PCA plots) can be browsed from the AltAnalyze interactive Results viewer (grey icon). For futher assistance contact the AltAnalyze help desk of view the online tutorial videos in YouTube.
Dear Nathan,
Thank you very much for such a nice share. I will follow your suggestions and will contact if needed.
Thank you,
Regards,