MsToGlf - Revision history

Thorfinn at 14:01, 26 July 2021

2021-07-26T14:01:49Z

← Older revision		Revision as of 16:01, 26 July 2021
Line 1:		Line 1:
	For the [[Korneliussen2013]] paper, we simulated data according to genotypes simulated from ms/msms output. For this we used the msToGlf program found in the 'misc/' subfolder of the angsd source directory.		For the [[Korneliussen2013]] paper, we simulated data according to genotypes simulated from ms/msms output. For this we used the msToGlf program found in the 'misc/' subfolder of the angsd source directory.

	This program assumes diploid samples.		This program assumes that the user is generating diploid samples, which means that the user should supply a msfile containing 2xNind haplotypes.
	=Brief Overview=		=Brief Overview=
	<pre>		<pre>

2016-02-05T15:44:06Z

Two populations

2015-12-16T15:30:22Z

← Older revision		Revision as of 17:30, 16 December 2015
Line 17:		Line 17:
	;-depthFile filename, This is useful if you want to force a different mean depth between individuals, remember to also use -nind if you use this option.		;-depthFile filename, This is useful if you want to force a different mean depth between individuals, remember to also use -nind if you use this option.
	; -pileup [int] 0 print GLF, 1 print mpileup format that can be read my ANGSD using the -pileup option		; -pileup [int] 0 print GLF, 1 print mpileup format that can be read my ANGSD using the -pileup option
			; -Nsites [int] 0 normal ms output, 1 msms -N [INT] output

	=Output format=		=Output format=

2015-11-12T18:19:24Z

← Older revision		Revision as of 20:19, 12 November 2015
Line 16:		Line 16:
	;-err errorrate, a value 0.005 corresponds to a 0.5% errorrate.		;-err errorrate, a value 0.005 corresponds to a 0.5% errorrate.
	;-depthFile filename, This is useful if you want to force a different mean depth between individuals, remember to also use -nind if you use this option.		;-depthFile filename, This is useful if you want to force a different mean depth between individuals, remember to also use -nind if you use this option.
			; -pileup [int] 0 print GLF, 1 print mpileup format that can be read my ANGSD using the -pileup option

	=Output format=		=Output format=

2015-05-05T18:59:33Z

Two populations

2014-08-13T17:49:12Z

Two populations

← Older revision		Revision as of 19:49, 13 August 2014
Line 74:		Line 74:
	We here specify a mean sequencing depth of 6, and an error rate of 0.5%. We only generate genotype likelihoods for the informative sites (-regLen 0), and generate a single output file.		We here specify a mean sequencing depth of 6, and an error rate of 0.5%. We only generate genotype likelihoods for the informative sites (-regLen 0), and generate a single output file.

	As the ~~earlier example with~~ angsd ~~you can use this file as input~~. ~~It even allows you to slice out specific individuals~~. ~~Say we wanted to calculate~~ .~~saf files for both populations, then we would do:~~		We now slice out the two populations into seperate files:
			<pre>
			angsd/misc/splitgl raw.glf.gz 20 1 12 >pop1.glf.gz
			angsd/misc/splitgl raw.glf.gz 20 13 20 >pop2.glf.gz
			</pre>

			And we run -doSaf 1 on both files
	<pre>		<pre>
	./angsd -glf ~~raw~~.glf.gz -nInd 20 -doSaf 1 -out pop1 ~~-from 0 -to 11~~ -fai hg19.fai -isSim 1		./angsd -glf pop1.glf.gz -nInd 12 -doSaf 1 -out pop1 -fai hg19.fai -isSim 1
	./angsd -glf ~~raw~~.glf.gz -nInd 20 -doSaf 1 -out pop2 ~~-from 12 -to 19~~ -fai hg19.fai -isSim 1		./angsd -glf pop2.glf.gz -nInd 8 -doSaf 1 -out pop2 -fai hg19.fai -isSim 1
	</pre>		</pre>

2014-08-13T17:18:57Z

Two populations

← Older revision		Revision as of 19:18, 13 August 2014
Line 85:		Line 85:
	realSFS 2dsfs pop1.saf pop2.saf 24 16 -P 4 >pop.em.ml		realSFS 2dsfs pop1.saf pop2.saf 24 16 -P 4 >pop.em.ml
	</pre>		</pre>
			The output is 25x17 matrix
	You can then read in the data in R and barplot the marginals		You can then read in the data in R and barplot the marginals

2014-07-31T09:55:06Z

Two populations

← Older revision		Revision as of 11:55, 31 July 2014
Line 77:		Line 77:

	<pre>		<pre>
	./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop1 -from 0 -to 11 -fai hg19.fai		./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop1 -from 0 -to 11 -fai hg19.fai -isSim 1
	./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop2 -from 12 -to 19 -fai hg19.fai		./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop2 -from 12 -to 19 -fai hg19.fai -isSim 1
	</pre>		</pre>

2014-07-31T09:54:46Z

Two populations

← Older revision		Revision as of 11:54, 31 July 2014
Line 77:		Line 77:

	<pre>		<pre>
	./angsd -~~sim1~~ raw.glf.gz -nInd 20 -doSaf 1 -out pop1 -from 0 -to 11		./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop1 -from 0 -to 11 -fai hg19.fai
	./angsd -~~sim1~~ raw.glf.gz -nInd 20 -doSaf 1 -out pop2 -from 12 -to 19		./angsd -glf raw.glf.gz -nInd 20 -doSaf 1 -out pop2 -from 12 -to 19 -fai hg19.fai
	</pre>		</pre>

2014-07-31T09:54:14Z

Standard neutral model

← Older revision		Revision as of 11:54, 31 July 2014
Line 40:		Line 40:
	./msToGlf -in msoutput -out msoutputWithInvar.gl -err 0.015 -depth 8 -nind 25 -singleOut 1 -regLen 1000000		./msToGlf -in msoutput -out msoutputWithInvar.gl -err 0.015 -depth 8 -nind 25 -singleOut 1 -regLen 1000000
	</pre>		</pre>
	These can be feed into angsd using -~~sim1~~ argument as input		These can be feed into angsd using -glf argument as input
	<pre>		<pre>
	../angsd -~~sim1~~ msoutputNoInvar.gl.glf.gz -nind 25 -doMajorMinor 1 -doMaf 1		../angsd -glf msoutputNoInvar.gl.glf.gz -nind 25 -doMajorMinor 1 -doMaf 1 -fai hg19.fai -isSim 1
	</pre>		</pre>
	If you do sample allele frequency based analysis '-doSaf' then the ancestral states are assumed to be 'A'.		If you do sample allele frequency based analysis '-doSaf' then the ancestral states are assumed to be 'A'.