The package has two programs:

(1) MQLS: for genotype data in QTDT/MERLIN format
Parameters:
-d dat file in QTDT/MERLIN format
-p ped file in QTDT/MERLIN format
-o output file
-f pvalue filter, larger pvalue will not be output
-k disease prevalence

Output columns:
Allele: reference allele
pTest: allele frequency estimator under alternative
pNull: allele frequency estimator under the NULL (if pTest > pNull, the allele has increased risk)
Freq1: Naive estimator of allele frequency in cases (calculated by gene counting)
Freq0: Naive estimator of allele frequency in controls (calculated by gene counting)
Chisq: Test statistics for association between marker and disease status
LOD: LOD score corresponding to the Chisq statistics
PValue: pvalue corresponding to the Chisq statistics

Here is a toy example pedigree data and its output:
pedigree file and dat file as the input.
association tests output.
message printout from the program.

Command line used for this example:
MQLS -p mqls.ped -d mqls.dat -o output_mqls.txt > printout_mqls.txt

(2) MQLS_dose: for imputation allele dosage in MACH format
Parameters:
-d dat file for disease affected status
-p ped file for disease affected status (only samples present in this file will be analyzed)
-o output file
-f pvalue filter, larger pvalue will not be output
-k disease prevalence
-s random seed for selection of one individual from each family to calculate the emprical
variance of allele copies
-e switcher for using emprical variance to replace the expected variance 0.5p(1-p) in the
paper. (default is ON, recommended)

--dosage imputated allele dosage output from MACH
format in each row: "famID->indID DOSE" followed by dosage for each marker
example: "100->1001 DOSE 1.93 1.82 0.35 ... "

--info marker infomation file output from MACH (only the first two columns are required)
format in each row: Marker ReferenceAllele
example: "rs11205006 T"
** the first row of this file should be the header **

Output columns:
Allele: reference allele
Rsq: imputation R-square (empirical variance divided by 0.5p(1-p)) used as an indicator for
imputation quality. The higher the better (we recommend using a Rsq>0.3 cut-off to
filter unreliable imputed SNPs).
pTest: allele frequency estimator under alternative
pNull: allele frequency estimator under the NULL (if pTest > pNull, the allele has increased risk)
Freq1: Naive estimator of allele frequency in cases (calculated by gene counting)
Freq0: Naive estimator of allele frequency in controls (calculated by gene counting)
Chisq: Test statistics for association between marker and disease status
LOD: LOD score corresponding to the Chisq statistics
PValue: pvalue corresponding to the Chisq statistics

Here is a toy example pedigree, MACH imputed data and its output:
pedigree file, dat file, MACH dosage data and info data as the input.
association tests output.
message printout from the program.

Command line used for this example:
MQLS_dose -p mqlsdose.ped -d mqlsdose.dat --dosage MACH.dose --info MACH.info -o output_mqlsdose.txt > printout_mqlsdose.txt

Comments and suggestions please email me: lianglim@umich.edu
Enjoy!