Matrix is singular warning in LD4M

[mja]

I've gotten the run_FMR_32traits.m script to run and now I'm trying to adapt it to my own GWAS results. I'm getting the error

Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN. 
> In LD4M (line 244)
  In run_FMR (line 68)

output a few dozen times, followed by

Out of memory. Type HELP MEMORY for your options.

Error in run_FMR (line 118)
        block=((jk-1)*blocksize+1:min(mm_regression,jk*blocksize)) + ...

This is running Matlab R2018 on a 32GB node.

I've made a plain text file for my GWAS results, where the first column is the numeric part of the rsID and the second column is a chisq value (calculated from the sumstats as log(OR)^2/SE^2). The first 5 rows look like:

2326918 0.2296
7929618 7.5625
66941928        0.0044
6977693 1.69
12364336        0.3554

I'm then loading it into Matlab setting up the inputs to run_FMR similar to what is in the example scripts:

% load the GWAS sumstats
gwas = dlmread('gwas_chisq.txt', '\t');

% first column are rsIDs (numeric), second column are chisq values
gwas_snps = gwas(:,1);
gwas_chisq = gwas(:,2);

% load FMR data files
load('FMR/matfiles/fourierLDscores.base.mat','SNPs','lF','l2','l4')
RefSNPs=vertcat(SNPs{:});
load('FMR/matfiles/1kg_LD.HM3.window1cm.noblocks.mat','RRb','LDSNPs')

% load FMR scripts
addpath('FMR/MATLAB/FMR')
addpath('FMR/MATLAB/otherfunctions')

% parameters
mm=length(lF);
no_blocks=100;
t_ratio_step=2;
ss=t_ratio_step.^(-7:5); %sigma^2 values of mixture cpts
tt=sqrt(ss); %sampling times
rel_wt=1;
sig_thresh_array=[30,100,300,1000];

% line up indices of SNPs between ref and gwas
[~,i2,i1]=intersect(RefSNPs,gwas_snps,'stable');

% run analysis
[ww,sigmasq,LD4Mout,warningflag] = ...
	run_FMR(gwas_chisq(i1),lF(i2,:),l2(i2),l4(i2),...
	ss,tt,'l2Weights',1./l2(i2),'l4Weights',1./l4(i2));