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nextflow.config
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params {
umi_count = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/RNA/filtered_feature_bc_matrix"
hto_mat = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/Hashtag/filtered_feature_bc_matrix"
outdir = "$projectDir/results/"
graphs = "$projectDir/graphs"
demultiplexing = "TRUE"
htoMode = "TRUE"
selection_method = "mean.var.plot"
number_features = 2000
assay = "HTO"
assayName = "HTO"
margin = 2
ndelim = "_"
normalisation_method = "CLR"
seed = 42
demulOutPath = "$projectDir/results"
nameOutputFile = "object"
quantile_hto = 0.99
kfunc = "clara"
nstarts = 100
nsamples = 100
init = "NULL"
objectOutHTO = "resultHTO"
nameOutputFileHTO = "classification_htodemux"
nameAssignmentFileHTO = "assignment_htodemux"
quantile_multi = 0.7
autoThresh = "FALSE"
maxiter = 5
qrangeFrom = 0.1
qrangeTo = 0.9
qrangeBy = 0.05
verbose = "TRUE"
multiSeqOutPath = "$projectDir/results/"
nameOutputFileMulti = "resultMulti_object"
nameClassificationFileMulti = "resultMulti"
visualisationSeurat = "TRUE"
ridgePlot = "TRUE"
ridgeNCol = 2
featureScatter = "TRUE"
scatterFeat1 = "NULL"
scatterFeat2 = "NULL"
vlnplot = "FALSE"
vlnFeatures = "NULL"
vlnLog = "TRUE"
tsne = "FALSE"
tseIdents = "Negative"
tsneInvert = "FALSE"
tsneVerbose = "FALSE"
tsneApprox = "FALSE"
tsneDimMax = 1
tsePerplexity = 100
heatmap = "FALSE"
heatmapNcells = 4000
hashedVisualisation = "TRUE"
rdsObject = "FALSE"
hashtag_data = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/Hashtag/filtered_feature_bc_matrix"
empty_drops_result = "$projectDir/results/"
rawData = "FALSE"
nameOutputFileDrops = "resultHashed"
nameOutputFileHashed = "resultHashed_object"
ambient = "NULL"
doubletMin = 2
minProp = 0.05
pseudoCount = 5
constAmbient = "FALSE"
doubletNmads = 3
confidenMin = 2
confidentNmads = 3
histogram = "TRUE"
plotLog = "TRUE"
demuxem_mode = "TRUE"
alpha = 0.0
alpha_noise = 1.0
tol = 1e-6
n_threads = 1
min_signal = 10.0
output_demux = "demuxEm"
hto_data = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/Hashtag/filtered_feature_bc_matrix"
priors_negative = 1/3
priors_singlet = 1/3
priors_doublet = 1/3
output_file = "hash_solo.csv"
output_plot = "hash_solo_plot.jpg"
doublet_detection = "TRUE"
soft = "False"
max_epochs = 100
lr = 0.001
output_solo = "solo_prediction.csv"
rna_raw = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/RNA/raw_feature_bc_matrix"
hto_raw = "/Users/mylenemarianagonzalesandre/Development/Data-cluster/Batch-1/Hashtag/raw_feature_bc_matrix"
niters = 10000
empty = "TRUE"
lower = 100
testAmbient = "FALSE"
alpha_empty = "NULL"
ignore = "NULL"
nameOutputEmpty = "emptyDropletsHashed"
nameObjectEmpty = "emptyDropletsObject"
max_time = 5.d
max_memory = 385.GB
// do not set to the max of the nodes otherwise some jobs might only run on the max nodes
max_cpus = 48
cleaning_raw = "FALSE"
general_assignment = "TRUE"
output_assignment = "general_assignment.csv"
output_classification = "general_classification.csv"
output_final = "final_report.csv"
}
process{
//For general processes
conda = "/opt/anaconda3/envs/demul"
time = 2.h
//memory = 5.GB
//cpus = 2
//withLabel: seurat_process{
// conda = "/home/icb/mariana.gonzales/miniconda3/envs/demul"
// time = 2.h
// memory = 5.GB
// cpus = 1
//}
// withName: HASHED_DROPS_DEMUL{
// conda = "/home/icb/mariana.gonzales/miniconda3/envs/demul"
// time = 2.h
// memory = 5.GB
// cpus = 1
//}
withName: SOLO{
conda = "/opt/anaconda3/envs/solo"
time = 40.h
memory = 9.GB
// cpus = 2
}
}