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tests.R
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source("helpers.R")
source("fun-input-analyze-data.R")
x <- load_existing_rdata("data/mousecounts_example.RData")
str(x)
# Normal example data
alldata <- read_csv("data/mousecounts_example.csv")
tmp = extract_count_data(alldata)
analysis_method="edgeR"
numgeneids = 2
tmp2 <- analyze_expression_data(alldata[1:200,], analysis_method="edgeR", numgeneids = 2)
glimpse(tmp2$data_long)
tmp2 <- analyze_expression_data(alldata[1:200,], analysis_method="voom", numgeneids = 2)
glimpse(tmp2$data_long)
tmp2 <- analyze_expression_data(alldata[1:200,], analysis_method="linear_model", numgeneids = 2)
glimpse(tmp2$data_long)
# One group
testdata <- read_csv("data/testdata_counts_onegroup.csv")
tmp3 <- analyze_expression_data(testdata, analysis_method="edgeR", numgeneids = 2)
glimpse(tmp3$data_long)
glimpse(tmp3$results)
tmp3 <- analyze_expression_data(testdata, analysis_method="voom", numgeneids = 2)
glimpse(tmp3$data_long)
glimpse(tmp3$results)
tmp3 <- analyze_expression_data(testdata, analysis_method="linear_model", numgeneids = 2)
glimpse(tmp3$data_long)
glimpse(tmp3$results)
# non-counts
testdata <- read_csv("data/testdata_noncounts.csv")
tmp4 <- analyze_expression_data(testdata, analysis_method="edgeR", numgeneids = 2)
head(tmp4$results)
dotplot_fun(data_long = tmp4$data_long,
geneids = tmp4$geneids,
genelabel="unique_id",
sel_group=tmp4$group_names,
sel_gene=tmp4$geneids$unique_id[1:2],
ytype="log2cpm")
gene_pcaplot(data_long= tmp4$data_long,
valuename= "log2cpm",
sampleid= tmp4$sampledata$sampleid,
groupdat= tmp4$sampledata[,"group",drop=FALSE],
pcnum = 1:2,
colorfactor="group")
rna_scatterplot(data_long = tmp4$data_long,
results = tmp4$results,
group_sel = tmp4$group_names,
valuename="log2cpm",
color_result_name = "Sign of FC",
results_test_name = unique(as.character(tmp4$results$test))[1],
color_low = "blue",
color_hi = "orange",
sel_genes = NULL
)
png("tmp.png") # can't render in rstudio at the moment
heatmap_render(
data_analyzed=tmp4,
yname = "log2cpm",
usesubset = FALSE,
rowcenter=TRUE,
subsetids = NULL,
orderby = "variation",
FDRcut=0.05,
maxgenes=50,
view_group=c("group1", "group2"),
view_samples=c("group1_1", "group1_2", "group2_1","group2_2"),
sel_test=unique(as.character(tmp4$results$test))[1],
heatmap_rowlabels=TRUE)
dev.off()
fs::file_delete("tmp.png")
# One replication
testdata <- read_csv("data/testdata_counts_onerep.csv")
tmp3 <- analyze_expression_data(testdata, analysis_method="edgeR", numgeneids = 2)
# need to add option for this somehow
# alldata <- read_csv("~/Downloads/joe515.csv")
# tmp = extract_count_data(alldata)
# tmp3 <- analyze_expression_data(alldata, analysis_method="edgeR")
# analyzed data not working
# sample heatmaps not working
testdata <- read_csv("data/testdata_analyzed_onecomparison.csv")
data_analyzed = load_analyzed_data(testdata, tmpgenecols = 1:2, tmpexprcols = 3:12,
tmpfccols = 13, tmppvalcols = 14, tmpqvalcols = 15, isfclogged = TRUE)
tmpdatlong = data_analyzed$data_long
(tmpynames = tmpdatlong%>%select(-unique_id,-sampleid,-group,-one_of("rep"))%>%colnames())
(tmpgroups = data_analyzed$group_names)
(tmpsamples = as.character(data_analyzed$sampledata$sampleid))
tmpdat = data_analyzed$results
(tmptests = unique(as.character(tmpdat$test)))
# Uploaded data
testdata <- load("data/testdata_counts_prot_uploaded.RData") # start_list
testdata <- load_existing_rdata("data/testdata_counts_prot_uploaded.RData")
rdata_filepath <- "data/mousecounts_example.RData"
testdata <- load_existing_rdata(rdata_filepath)