Source Data and Code for "GPSeq maps the radial organization of eukaryotic genomes along the nuclear periphery-center axis"
Here contains the source data (in .rds) and source code (in .r) to reproduce the figures of manuscript of Genomics loci Positioning by Sequencing (GPSeq) submitted to Nature Protocols. All supplied codes are written in R language. Each script uses the corresponding data as input and generate plots described in the manuscript. Figure 4. Examples of successful gradual radial DNA digestion in cells and nuclei. This figure shows the fluorescence signal intensity of nuclei labelled by YFISH from the periphery to the centre after being digested by DpnII at various time points (8 timepoints, from 30 sec to 64 min). Figure 5. Representative TapeStation profiles for the main QC steps during GPSeq library preparation This figure shows the DNA or RNA analysed on Tapestation at different steps during GPSeq protocols. These steps include (gDNA extraction, sonication, in vitro transcription and final libraries). This aims to guide the user to obtain optimal size distribution of GPSeq library. Figure 6. Workflow and representative outputs from the GPSeq data analysis pipeline This figure shows an exampbletary output of the nextflow-gpseq pipline using the raw data. It includes a barplot describing the amount of reads after various steps of the pipeline, a heatmap describing the reproducibility of two biological replicates using Spearman's correlation coefficient and a pizza plot and boxplot illustrating the distribution of GPSeq score (from 0 at the nuclear periphery to 1 at the nuclear centre). Figure 7. Comparison of GPSeq performed on cells, nuclei and swelling of cells and nuclei This figures focuses on demonstrating the robustness and high reproducibility of samples prepared in different conditions (intact cells grown on coverslip, swollen cells grown on coverslip, extracted nuclei spotted on coverslip and swollen extracted nuclei spotted on coverslip).
Genomics
Genome structure and regulation
Genomics and transcriptomics
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Landningssida för datasetet
Karolinska Institutet