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upper quantile normalization code

input:
xena genomicMatrix file -supplied on the command line
gene file (each row is a gene) - supplied on the command line

output:
upper quantile normalized genomicMatrix file,
the offset parameter for each sample

  1. download a gene expression xena genomicMatrix on a TCGA data, such as http://ec2-52-23-185-93.compute-1.amazonaws.com/datapages/?dataset=TCGA.COAD.sampleMap/HiSeqV2&host=https://tcga.xenahubs.net
    sample ids are column header, gene names are on the first column'

  2. using the unit in the url to revert back the value to before the log transformation, e.g. "log2(norm_count +1)" -> revert back to "norm_count" , where 1 is the pseudo count

  3. Using the reverted values, for each column in the file downloaded in 1, the script will only rank the genes belong to the gene file, identify the upper (top) 75% ranked value (100% is the gene with the highest value), assign this as the upper quantile value for this column, then divide every value in the column by the upper quantile value, multiply by 1 million, plus the pseudo count value (e.g. 1 in the example), then log2 transform

log2(x+1) => x => log2(x/uq * 1E6 +1)

  1. a good gene list genes that are expression in at least 90% TCGA samples and 90% GTEx samples: is https://github.com/ucscXena/python-scripts/blob/master/geneLists/GTEX_TCGA_genes

  2. output the upper quantile normalized matrix

  3. output the upper quantile value for each column in a separate file in this format
    column id upper quantile value
    column id upper quantile value

  4. optional: include an optional probeMap file for the situation the download genomicMatrix file does not use gene names. The probeMap file can be downloaded, containing mapping information between gene and first column in the matrix.

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