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STochastic Rank Aggregation for the Identification of Neuromarkers
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README.md
ami_kendall_plots.ipynb
ami_script.m
anat_parcellation.m
anatomicalClusterDistance.m
calcDOCresample.m
calc_means.m
calc_medoids.m
consensus_cl.m
filterDegree.m
filter_consensus_mat.m
filter_consensus_matrix.m
input_topklists.m
input_topklists_anat.m
input_topklists_cluster.m
input_topklists_perm.m
input_topklists_subsample.m
jaccard.m
jaccard_consensus.m
kendall+jaccard_script.R
mask4mm.mat
md_anatvoi_abs_median_topranks_d8-8-8v10.mat
md_cluster_abs_median_topranks_d8-10-8v10.mat
md_ext76_kmeans_f05s3_toprank_d8-10-8v10_abs_median.mat
md_filters.mat
md_kmeans_consensus_filter_ranks_abs_median.mat
md_kmeans_consensus_filter_stability.m
md_kmeans_consensus_filter_subsamples.m
md_kmeans_consensus_stability.m
md_kmeans_sol_consensus.mat
md_split_train.mat
medianvois.mat
multi_disease_DMN.mat
topklists_perm.R
topklists_script.R
topklists_smp.R

README.md

STRAIN

STochastic Rank Aggregation for the Identification of Neuromarkers

bioRxiv preprint

Required libraries:

  • R: R.matlab, TopKLists, parallel
  • python: numpy, scipy, sklearn
  • matlab: NeuroElf_v09c
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