>program name 
GLAM
>data set
dm01
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm01.fasta
Repeat masking step II : runnseg dm01.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm02
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm02.fasta
Repeat masking step II : runnseg dm02.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm03
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm03.fasta
Repeat masking step II : runnseg dm03.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm04
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm04.fasta
Repeat masking step II : runnseg dm04.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm05
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm05.fasta
Repeat masking step II : runnseg dm05.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm06
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm06.fasta
Repeat masking step II : runnseg dm06.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm07
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm07.fasta
Repeat masking step II : runnseg dm07.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
dm08
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -dr dm08.fasta
Repeat masking step II : runnseg dm08.fasta.masked
Cut sequences into 500bp pieses, with the first cutting position randomly chosen between 250-750
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.8 times the maximum score.
>data set
hm01
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm01.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm02
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm02.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm03
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm03.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm04
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm04.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm05
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm05.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm06
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm06.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm07
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm07.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm08
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm08.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm09
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm09.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm10
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm10.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm11
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm11.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm12
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm12.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm13
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm13.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm14
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm14.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm15
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm15.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm16
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm16.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm17
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm17.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm18
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm18.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm19
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm19.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm20
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm20.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm21
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm21.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm22
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm22.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm23
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm23.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm24
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm24.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm25
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm25.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
hm26
>parameters
a=4
b=20
t=1
l=ON
>preprocessing
Repeat masking : dust hm26.fasta 15
>postprocessing
Iteratively run GLAM with shrinking motif width parameters. Stop at the first state that 
further shrinking did not cause major disruption to the motif reported.
>data set
mus01
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus01.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus02
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus02.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus03
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus03.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus04
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus04.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus05
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus05.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus06
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus06.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus07
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus07.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus08
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus08.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus09
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus09.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus10
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus10.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus11
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus11.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
mus12
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking step I  : RepeatMasker -xsmall -m mus12.fasta
Repeat masking step II : runnseg mus*.fasta.masked
>postprocessing
None
>data set
yst01
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst01.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst02
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst02.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst03
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst03.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst04
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst04.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst05
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst05.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst06
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst06.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst07
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst07.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst08
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst08.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst09
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst09.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.
>data set
yst10
>parameters
a=4
b=10
t=1
l=ON
>preprocessing
Repeat masking: dust yst10.fasta
>postprocessing
Construct a position specific base count matrix from GLAM results and scan the sequence with 
this matrix using Possum. Set the score threshold to 0.6 times the maximum score.