ACT IntegratedExample - Revision history

Justin.jee at 18:20, 23 October 2010

2010-10-23T18:20:27Z

← Older revision		Revision as of 18:20, 23 October 2010
Line 69:		Line 69:

	</pre>		</pre>

			The pink bars correspond to the range of covered values as determined by saturating the files in every possible order.

	[[Image:Saturation_wg_t20.png\|x500px]]		[[Image:Saturation_wg_t20.png\|x500px]]

Justin.jee at 15:36, 22 October 2010

2010-10-22T15:36:28Z

@@ Line 18: / Line 18: @@
 Using ACT.py, we get a four-column file which can be plotted in Excel or using R:
 [[Image:Agg_wg.png]]
@@ Line 34: / Line 36: @@
 The resulting correlation matrix can be plotted in R using the heatmap function:
 [[Image:Corr_wg_heatmap.png]]
@@ Line 44: / Line 58: @@
 Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.
 [[Image:Saturation_wg_t20.png|x500px]]

Justin.jee at 16:51, 10 September 2010

2010-09-10T16:51:41Z

← Older revision		Revision as of 16:51, 10 September 2010
Line 13:		Line 13:
	*Aggregation		*Aggregation

	After downloading the agg-py package, it is necessary to download an annotations file with coordinates you want to aggregate over. For this example, we used all transcription start sites as taken from build 18 of the human genome annotated by the gencode project.		After downloading the agg-py package, it is necessary to download an annotations file with coordinates you want to aggregate over. For this example, we used all transcription start sites as taken from build 18 of the human genome annotated by the gencode project. For convenience/testing purposes, we have provided a parsed version of the gencode gene annotations which is compatible with act here:

			http://act.gersteinlab.org/gencode.coords

	Using ACT.py, we get a four-column file which can be plotted in Excel or using R:		Using ACT.py, we get a four-column file which can be plotted in Excel or using R:

Justin.jee at 16:47, 10 September 2010

2010-09-10T16:47:04Z

← Older revision		Revision as of 16:47, 10 September 2010
Line 43:		Line 43:
	Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.		Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.

	[[Image:Saturation_wg_t20.png\|~~x300px~~]]		[[Image:Saturation_wg_t20.png\|x500px]]

Justin.jee at 16:46, 10 September 2010

2010-09-10T16:46:20Z

← Older revision		Revision as of 16:46, 10 September 2010
Line 43:		Line 43:
	Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.		Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.

	[[Image:Saturation_wg_t20.png\|~~size=~~x300px]]		[[Image:Saturation_wg_t20.png\|x300px]]

Justin.jee at 16:45, 10 September 2010

2010-09-10T16:45:47Z

← Older revision		Revision as of 16:45, 10 September 2010
Line 43:		Line 43:
	Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.		Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.

	[[Image:Saturation_wg_t20.png]]		[[Image:Saturation_wg_t20.png\|size=x300px]]

Justin.jee at 16:44, 10 September 2010

2010-09-10T16:44:25Z

← Older revision		Revision as of 16:44, 10 September 2010
Line 37:		Line 37:
	*Saturation		*Saturation

	It is necessary to convert the wig files to bed files without a "signal" component. The following script takes wig files and converts them into bed files, with coordinates representing the regions of the signal track which are above a certain threshold (in this case 0).		It is necessary to convert the wig files to bed files without a "signal" component. The following script takes wig files and converts them into bed files, with coordinates representing the regions of the signal track which are above a certain threshold (in this case 20).

	http://act.gersteinlab.org/wig2bed.pl		http://act.gersteinlab.org/wig2bed.pl

	Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.		Go to saturation.sh and change the input files to PolII.bed and Stat1.bed. It will also probably be necessary to change the alloted memory (in the second of the final java command in saturation.sh, change the numbers in the second field from 128 to 4096). Since there are only two signal tracks, the Saturation and Correlation analyses provide overlapping information.

			[[Image:Saturation_wg_t20.png]]

Justin.jee at 01:26, 10 September 2010

2010-09-10T01:26:25Z

← Older revision		Revision as of 01:26, 10 September 2010
Line 12:		Line 12:

	*Aggregation		*Aggregation

			After downloading the agg-py package, it is necessary to download an annotations file with coordinates you want to aggregate over. For this example, we used all transcription start sites as taken from build 18 of the human genome annotated by the gencode project.

			Using ACT.py, we get a four-column file which can be plotted in Excel or using R:

			[[Image:Agg_wg.png]]

	*Correlation		*Correlation

Justin.jee at 19:35, 9 September 2010

2010-09-09T19:35:13Z

← Older revision		Revision as of 19:35, 9 September 2010
Line 15:		Line 15:
	*Correlation		*Correlation

	It is necessary to convert the signal tracks from sgr to wig format. A script which does this can be found here:		For this example, since we are dealing with signal tracks rather than SNP positions or a bed file of genomic locations, we will use the correlation tool found in corr-sat-bundle to do the correlation calculation. First, it is necessary to convert the signal tracks from sgr to wig format. A script which does this can be found here:

	http://act.gersteinlab.org/sgr2wig.pl		http://act.gersteinlab.org/sgr2wig.pl

	The resulting correlation matrix can be plotted in R:		Once we have converted both the PolII and Stat1 sgr files to wig files, we can change the parameters in correlation.sh so that the input files are "PolII.wig" and "Stat1.wig"

			In addition, it is important to change config.txt so that the list of genomic regions includes all chromosomes, including mitochondrial sequences. (When the package is first downloaded, all lines except for the one denoting chromosome 22 are commented out).

			Once both the correlation.sh and config.txt files have been modified, we can run correlation.sh. This will produce an output file with a correlation matrix describing the correlation coefficients between PolII and Stat1 signal.

			The resulting correlation matrix can be plotted in R using the heatmap function:

	[[Image:Corr_wg_heatmap.png]]		[[Image:Corr_wg_heatmap.png]]

Justin.jee at 19:06, 9 September 2010

2010-09-09T19:06:51Z

← Older revision		Revision as of 19:06, 9 September 2010
Line 18:		Line 18:

	http://act.gersteinlab.org/sgr2wig.pl		http://act.gersteinlab.org/sgr2wig.pl

			The resulting correlation matrix can be plotted in R:

			[[Image:Corr_wg_heatmap.png]]

	*Saturation		*Saturation