# Pan-Cancer Analyses Reveal Genomic Features of FOXM1 Overexpression in Cancer
## Materials and Methods
### RNA Sequencing (RNA-seq) Analysis  
RNA was isolated from cell lines according to the method described above. The RNA samples were transported to the UNMC DNA Sequencing Core Facility. RNA samples were analyzed with respect to purity and potential degradation. Purity and concentration were assessed by measurement of the A260/280 ratios using a Nanodrop instrument (Thermo Scientific, Nanodrop Products) instrument and only those samples with values of 1.8 to 2.0 underwent further processing. Potential degradation of the samples was assessed by analysis of 200 ng of the RNA with a Fragment Analyzer (Agilent) and only intact RNA samples were used to generate sequencing libraries. Sequencing libraries were generated by the UNMC NGS Core beginning with 1 ug of total RNA from each sample using the TruSeq V2 RNA sequencing library kit from Illumina following recommended procedures (Illumina, San Diego, CA, USA). Resultant libraries were assessed for size of insert by analysis of an aliquot of each library on a Bioanalyzer instrument (Agilent Technologies, Santa Clara, CA, USA). Each library had a unique indexing identifier barcode allowing the individual libraries to be multiplexed together for efficient sequencing. Multiplexed libraries (12 samples per pool) were sequenced across 2 lanes of the HiSeq 2500 DNA Analyzer (Illumina) to generate a total of approximately 20 million 75 bp single reads for each sample. During sequencing, the quality was continually monitored regarding cluster number and fluorescence intensity and percentages of reads passing filter with a Q30 score. Following sequencing, samples were demultiplexed to produce FASTQ files. The UNMC Epigenomics Core Facility processed the resulting sequence files based on the following steps. Adaptor sequences and low quality (Phred score: 20) ends were trimmed from sequences using the Trim Galore software package ([[http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/](http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)]([http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/](http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/))). Resulting FASTQ files were aligned to the human genome (NCBI37/hg19) using the software TopHat (v2.0.8) ([[http://ccb.jhu.edu/software/tophat/index.shtml](http://ccb.jhu.edu/software/tophat/index.shtml)]([http://ccb.jhu.edu/software/tophat/index.shtml](http://ccb.jhu.edu/software/tophat/index.shtml))). The software Cufflinks (v2.1.1) [[http://cole-trapnell-lab.github.io/cufflinks/](http://cole-trapnell-lab.github.io/cufflinks/)]([http://cole-trapnell-lab.github.io/cufflinks/](http://cole-trapnell-lab.github.io/cufflinks/)) was used to estimate the expression values, and Cuffdiff (v2.1.1) was used to determine differential expression. Venn diagrams were generated with Venn Diagrams software (Bioinformatics & Evolutionary Genomics-Ghent University [[http://bioinformatics.psb.ugent.be/webtools/Venn/](http://bioinformatics.psb.ugent.be/webtools/Venn/)]([http://bioinformatics.psb.ugent.be/webtools/Venn/](http://bioinformatics.psb.ugent.be/webtools/Venn/))).