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RegulatoryGenomicsGroup / chicdiff

A differential caller for capture Hi-C data
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Order of test and control entry for fold change interpretation #21

Open wilsoner2175 opened 7 months ago

wilsoner2175 commented 7 months ago

Hi,

I just want to clarify the interpretation of fold change for the differential loops called in my experimental data. I ran the data as shown below. Is fold change reported with respect to the first or second entry in my countdata and ChicagoData list? In my case, would positive fold change reflect increased interactions in the CD34 samples compared to AML samples?

countData <- list(
          CD34 =  c(CD34_1 = file.path(testDataPath_CD34, "data_CaptureC.chinput"),
            CD34_2 = file.path(testDataPath_CD34, "data_CaptureC.chinput")
            ),

          AML = c(AML1= file.path(testDataPath_IDHmut, "data_CaptureC.chinput"),
            AML2 = file.path(testDataPath_IDHmut, "data_CaptureC.chinput"),
            AML3 = file.path(testDataPath_IDHmut, "data_CaptureC.chinput"),
            AML4 = file.path(testDataPath_IDHmut, "data_CaptureC.chinput")
            )
  )

testDataPath_rda <- file.path(dataPath, "CD34_vs_AML/data")

chicagoData <- list(
            CD34 =  c(CD34_1 = file.path(testDataPath_rda, "data_CaptureC.Rds"),
            CD34_1= file.path(testDataPath_rda, "data_CaptureC.Rds")
            ),

            AML = c(AML1 = file.path(testDataPath_rda, "data_CaptureC.Rds"),
            AML2 = file.path(testDataPath_rda, "data_CaptureC.Rds"),
            AML3 = file.path(testDataPath_rda, "data_CaptureC.Rds"),
            AML4 = file.path(testDataPath_rda, "data_CaptureC.Rds")
            )
  )

chicdiff.settings <- setChicdiffExperiment(designDir = testDesignDir, chicagoData = chicagoData, countData = countData, peakfiles = peakFiles, outprefix="CD34_vs_AML")

output <- chicdiffPipeline(chicdiff.settings)

saveRDS(output, paste0("chicdiff_results.Rds"))