Computational protocol: Identification of Cdca7 as a novel Notch transcriptional target involved in hematopoietic stem cell emergence

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Protocol publication

[…] For calling the enriched peaks we used two independent algorithms, namely Chipper91 and Bioconductor92 package (version 2.7) iChIP (both iChIP1 and iChIP2; version 1.4.0). In the latter, background was corrected and Loess normalized data were used as input. For this purpose, the Bioconductor package Limma 93 was used. Multiple test-corrected (false discovery rate [FDR]; cutoff 0.05 for Chipper and 0.01 for iChIP) enriched probes were annotated to Ensembl (version 60) genes94. The RBPj target genes identified by both Chipper and iChIP were put in a highly confident RBPj targets dataset. Of this dataset, the region −5 to 5 kb from the TSS was scanned using the STORM program (version 9.4; 95) and Transfac RBPj position frequency matrix96 (using V$RBPJK_01, M01112) for putative in silico RBPj binding site determination. GO () functional and pathway (KEGG) enrichment analysis of genes was done by using GiTools97. Functional annotation of differentially target genes is based on GO (), as extracted from Ensembl () and KEGG pathway databases (). Accordingly, all genes are classified into the ontology categories biological process (GOBP) and pathways when possible. We have taken only the GO/pathway categories that have at least 10 genes annotated. We used Gitools for enrichment analysis and heat map generation (). Resulting p-values were adjusted for multiple testing using the Benjamini and Hochberg method of FDR (). All data have been deposited in the GEO database (accession no. GSE52094; included in Table S1). […]

Pipeline specifications

Software tools limma, Gitools
Databases KEGG KEGG PATHWAY
Application ChIP-on-chip analysis
Organisms Danio rerio, Homo sapiens
Diseases Hematologic Neoplasms