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PoisonAlien / maftools

Summarize, Analyze and Visualize MAF files from TCGA or in-house studies.
http://bioconductor.org/packages/release/bioc/html/maftools.html
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Can we use our pre computed occurrence data to in maftools to plot Somatic Interaction? #866

Closed kcmtest closed 1 year ago

kcmtest commented 2 years ago

Describe the issue I would like to use the Somatic Interaction function of the maftools with my pre calculated data which was obtained from cbioportal

The small subset of my data looks like this

dput(head(a,20))
    structure(list(A = structure(c(4L, 34L, 13L, 13L, 26L, 26L, 18L, 
    37L, 26L, 18L, 51L, 37L, 44L, 26L, 18L, 51L, 41L, 26L, 18L, 51L
    ), .Label = c("ADAMTS15", "AFAP1L1", "ARHGEF15", "ATP6V0E2", 
    "BLID", "CADM1", "CASP1", "CAV2", "CBR1", "CD74", "CYP2E1", "EFNB3", 
    "ETS2", "FAM83G", "FLNC", "GALNS", "GBP6", "GFRA3", "GJC2", "GLB1L2", 
    "GPNMB", "GRAP", "HYOU1", "IGF2BP3", "IL12B", "JAKMIP2", "KCNIP1", 
    "KCNK1", "KCNMB1", "KIAA0087", "KIAA1549", "MICALL2", "MMP7", 
    "MX1", "NRGN", "OR2A9P", "OR9A4", "PATE2", "PATE4", "PCBP3", 
    "PCDH12", "PCDHB16", "PCDHGA3", "PDIA4", "PGBD5", "PRDM6", "PRR15", 
    "PRRT4", "PTGFR", "RARRES2", "RELL2", "RHOBTB3", "ROBO3", "RRAD", 
    "SCIN", "SCN4B", "SDR42E1", "SH3TC2", "SIDT2", "SLC22A4", "SLC28A3", 
    "SLC35F3", "SMO", "SNX24", "SORL1", "SPATA9", "THSD7A", "TLE1", 
    "TRIM36", "TRPM6", "UNCX", "VENTX", "VWA5A", "ZBTB46", "ZFHX3", 
    "ZNF853", "ZNRF1"), class = "factor"), B = structure(c(51L, 2L, 
    35L, 2L, 17L, 52L, 52L, 45L, 42L, 42L, 42L, 48L, 48L, 61L, 61L, 
    61L, 61L, 72L, 72L, 72L), .Label = c("AFAP1L1", "AGPAT3", "ARHGEF15", 
    "ATP6V0E2", "BLID", "CADM1", "CASP1", "CAV2", "CBR1", "CD74", 
    "CHRNB1", "CNIH3", "CRTAM", "FLNC", "GAS8", "GBP6", "GFRA3", 
    "GJC2", "GKAP1", "GLB1L2", "GPNMB", "GRAP", "HYOU1", "IGF2BP3", 
    "IL12B", "JAKMIP2", "KCNK1", "KCNMB1", "KIAA0087", "KIAA1549", 
    "LGALS9C", "MCOLN2", "MEST", "MMP7", "MX1", "NRGN", "NUDT7", 
    "OR2A9P", "PATE2", "PATE4", "PCBP3", "PCDH12", "PCDHGA12", "PCDHGA3", 
    "PDIA4", "PRDM6", "PRR15", "PRRT4", "PSAT1", "PTGFR", "RARRES2", 
    "RELL2", "RHOBTB3", "ROBO3", "RRAD", "SCIN", "SCN4B", "SDR42E1", 
    "SH3TC2", "SIDT2", "SLC22A4", "SLC29A4", "SLC35F3", "SMO", "SNX24", 
    "SORL1", "SOX18", "SPATA9", "SYCE1", "THSD7A", "TLE1", "TRIM36", 
    "UNCX", "UTF1", "VWA5A", "ZFHX3", "ZNF853"), class = "factor"), 
        Neither = c(185L, 185L, 183L, 183L, 186L, 186L, 186L, 186L, 
        186L, 186L, 186L, 186L, 186L, 186L, 186L, 186L, 186L, 186L, 
        186L, 186L), A.Not.B = c(0L, 0L, 2L, 2L, 0L, 0L, 0L, 0L, 
        0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), B.Not.A = c(0L, 
        0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
        0L, 0L, 0L, 0L), Both = c(6L, 6L, 6L, 6L, 5L, 5L, 5L, 5L, 
        5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), Log2.Odds.Ratio = structure(c(1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L), .Label = ">3", class = "factor"), p.Value = structure(c(1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L), .Label = "<0.001", class = "factor"), q.Value = structure(c(1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L), .Label = c("<0.001", "0.001", "0.003", "0.006", 
        "0.010", "0.012", "0.031"), class = "factor"), Tendency = structure(c(1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L), .Label = "Co-occurrence", class = "factor")), row.names = c(NA, 
    20L), class = "data.frame")

I would like to generate similar plot like this , is it possible for me to do the same? using any function from maftools

download

Command Please post your commands and the output (errors or any unexpected output)

Session info Run sessionInfo() and post the output below

PoisonAlien commented 1 year ago

Hi, Sorry for the late reply. Unfortunately, It is not a suitable input for generating the plot. P/Q values and odds ratios are not on a continuous scale.