<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recent changes to Home</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>Recent changes to Home</description><atom:link href="https://sourceforge.net/p/indelldplot/wiki/Home/feed" rel="self"/><language>en</language><lastBuildDate>Fri, 03 Jul 2015 12:09:40 -0000</lastBuildDate><atom:link href="https://sourceforge.net/p/indelldplot/wiki/Home/feed" rel="self" type="application/rss+xml"/><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v7
+++ v8
@@ -1,6 +0,0 @@
-The generation of Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) was originated from the observation that high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) emerged in GWAS SNPs and the underexplored status of indel cis-eQTLs for GWAS. We believe that the integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, PExFInS to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.
-
-PExFInS can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project. PExFInS can annotate these high LD variants with ANNOVAR. In addition, PExFInS can map these variants to Ensembl Regulatory Regions. Furthermore, IndelDplot can carry out cis-acting expression quantitative trait loci (cis-eQTL) analysis with genome-wide expression dataset as well as the corresponding next generation sequencing dense genotyping of lymphoblastoid cell lines (LCLs) provided by the 1000 Genomes Project among 432 individuals across six population groups. PExFInS can also map these high LD variants to known Ensembl regulatory features.
-
-PExFInS is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, PExFInS will output all high LD variants as well as the annotation data and eQTL data. Additionally, PExFInS can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, PExFInS can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, PExFInS can utilize a powerful annotation tool ANNOVAR to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
-
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Fri, 03 Jul 2015 12:09:40 -0000</pubDate><guid>https://sourceforge.net5dc6e3d2fbb904b6c68592b430b9a2933090eb6b</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v6
+++ v7
@@ -1,7 +1,6 @@
+The generation of Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) was originated from the observation that high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) emerged in GWAS SNPs and the underexplored status of indel cis-eQTLs for GWAS. We believe that the integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, PExFInS to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.

-The generation of IndelLDplot was originated from the observation that high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) emerged in GWAS SNPs and the underexplored status of indel cis-eQTLs for GWAS. We believe that the integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.
+PExFInS can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project. PExFInS can annotate these high LD variants with ANNOVAR. In addition, PExFInS can map these variants to Ensembl Regulatory Regions. Furthermore, IndelDplot can carry out cis-acting expression quantitative trait loci (cis-eQTL) analysis with genome-wide expression dataset as well as the corresponding next generation sequencing dense genotyping of lymphoblastoid cell lines (LCLs) provided by the 1000 Genomes Project among 432 individuals across six population groups. PExFInS can also map these high LD variants to known Ensembl regulatory features.

-IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project. IndelLDplot can annotate these high LD variants with ANNOVAR. In addition, IndelLDplot can map these variants to Ensembl Regulatory Regions. Furthermore, IndelDplot can carry out cis-acting expression quantitative trait loci (cis-eQTL) analysis with genome-wide expression dataset as well as the corresponding next generation sequencing dense genotyping of lymphoblastoid cell lines (LCLs) provided by the 1000 Genomes Project among 432 individuals across six population groups. IndelLDplot can also map these high LD variants to known Ensembl regulatory features.
+PExFInS is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, PExFInS will output all high LD variants as well as the annotation data and eQTL data. Additionally, PExFInS can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, PExFInS can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, PExFInS can utilize a powerful annotation tool ANNOVAR to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.

-IndelLDplot is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
-
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Wed, 10 Jun 2015 06:38:06 -0000</pubDate><guid>https://sourceforge.net47f08101b25504e981e9ac5c9cd3a07e7a70244e</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v5
+++ v6
@@ -1,6 +1,7 @@
-Given the high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) in GWAS SNPs and the underexplored indel cis-eQTLs for GWAS, integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.

-IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project; then map these high LD variants to cis-eQTLs and known Ensembl regulatory features, by which the potential functional relevance of user-queried SNPs could be revealed.
+The generation of IndelLDplot was originated from the observation that high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) emerged in GWAS SNPs and the underexplored status of indel cis-eQTLs for GWAS. We believe that the integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.

-IndelLDplot is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR33 to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
+IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project. IndelLDplot can annotate these high LD variants with ANNOVAR. In addition, IndelLDplot can map these variants to Ensembl Regulatory Regions. Furthermore, IndelDplot can carry out cis-acting expression quantitative trait loci (cis-eQTL) analysis with genome-wide expression dataset as well as the corresponding next generation sequencing dense genotyping of lymphoblastoid cell lines (LCLs) provided by the 1000 Genomes Project among 432 individuals across six population groups. IndelLDplot can also map these high LD variants to known Ensembl regulatory features.

+IndelLDplot is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
+
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:52:11 -0000</pubDate><guid>https://sourceforge.net06418e0985a7315ea1a428344db85ed117cb1a24</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v4
+++ v5
@@ -1,3 +1,6 @@
-Given the high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) in GWAS SNPs and the underexplored indel cis-eQTLs for GWAS, integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.
-IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project; then map these high LD variants to cis-eQTLs and known Ensembl regulatory features, by which the potential functional relevance of user-queried SNPs could be revealed. This strategy is illustrated in Figure 4a. The high LD variant 3 localized in an Ensembl regulatory region and also being a LCL cis-eQTLs can be prioritized as a potentially functional variant which can tag the GWAS SNP of interest and be brought forward for replication in another cohort. Additionally, the parent gene of variant 3 can be applied for functional validation using molecular biology or cellular biology techniques.
-IndelLDplot is written in SAS statistical language (Figure 4b). A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR33 to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
+Given the high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) in GWAS SNPs and the underexplored indel cis-eQTLs for GWAS, integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs. 
+
+IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project; then map these high LD variants to cis-eQTLs and known Ensembl regulatory features, by which the potential functional relevance of user-queried SNPs could be revealed.
+
+IndelLDplot is written in SAS statistical language. A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR33 to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
+
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:36:17 -0000</pubDate><guid>https://sourceforge.netd6a992cd09197e54034cf5e2bdf34ecdca20b309</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:15:41 -0000</pubDate><guid>https://sourceforge.neta80be218147d04e701062e4b5dcb51b3dbdfde2e</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:15:34 -0000</pubDate><guid>https://sourceforge.nete0c984fd01af8ddf7c2e8a110f34d827fe0594f8</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v1
+++ v2
@@ -1,8 +1,3 @@
-Welcome to your wiki!
-
-This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].
-
-The wiki uses [Markdown](/p/indelldplot/wiki/markdown_syntax/) syntax.
-
-[[members limit=20]]
-[[download_button]]
+Given the high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) in GWAS SNPs and the underexplored indel cis-eQTLs for GWAS, integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs.
+IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project; then map these high LD variants to cis-eQTLs and known Ensembl regulatory features, by which the potential functional relevance of user-queried SNPs could be revealed. This strategy is illustrated in Figure 4a. The high LD variant 3 localized in an Ensembl regulatory region and also being a LCL cis-eQTLs can be prioritized as a potentially functional variant which can tag the GWAS SNP of interest and be brought forward for replication in another cohort. Additionally, the parent gene of variant 3 can be applied for functional validation using molecular biology or cellular biology techniques.
+IndelLDplot is written in SAS statistical language (Figure 4b). A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR33 to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:15:15 -0000</pubDate><guid>https://sourceforge.netedb8b4d81fc39ce7b53d6b515bfba430b1187771</guid></item><item><title>Discussion for Home page</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;p&gt;Given the high proportion of cis-acting expression quantiative trait loci (cis-eQTLs) in GWAS SNPs and the underexplored indel cis-eQTLs for GWAS, integration of cis-eQTLs, especially indel cis-eQTLs, with candidate disease-associated variants generated from GWAS could facilitate the identification of causal genes or disease mechanisms. On the other hand, the biological information encoded in human genome, such as regulatory features from the Ensembl regulatory database, will be conductive in pinpointing functional causal variant(s) for the disease association. Thus, we generated a pipeline, IndelLDplot to integrate our LCL cis-eQTL data, along with publicly available cis-eQTL datasets derived from lung tissues, human monocytes, dendritic cells, blood, and LCLs. &lt;/p&gt;
&lt;p&gt;IndelLDplot can be utilized to search for high linkage disequilibrium (LD) variants, including indels, with user-queried SNPs using the deep sequence data from the 1000 Genomes (1KG) project; then map these high LD variants to cis-eQTLs and known Ensembl regulatory features, by which the potential functional relevance of user-queried SNPs could be revealed. This strategy is illustrated in Figure 4a. The high LD variant 3 localized in an Ensembl regulatory region and also being a LCL cis-eQTLs can be prioritized as a potentially functional variant which can tag the GWAS SNP of interest and be brought forward for replication in another cohort. Additionally, the parent gene of variant 3 can be applied for functional validation using molecular biology or cellular biology techniques.&lt;/p&gt;
&lt;p&gt;IndelLDplot is written in SAS statistical language (Figure 4b). A total of seven SAS macros were created to perform LD analysis, eQTL analysis, and regulatory feature mapping. These macros can work along or in combination to solve complicated tasks. With the input dbSNP rs ID(s) or chromosome range, IndelLDplot will output all high LD variants as well as the annotation data and eQTL data. Additionally, IndelLDplot can provide genotyping data required by Haploview to draw the LD plot for input variants and LD derived SNPs and indels. For example, if users are interested in LD pattern among interested variants and previously published GWAS SNPs, IndelLDplot can retrieve genotypes of all these variants and examine LD pattern and haplotype blocks among these variants. Furthermore, IndelLDplot can utilize a powerful annotation tool ANNOVAR33 to annotate the input SNPs and their high LD variants with annotation databases from the UCSC Genome Browser and map these variants to RefSeq genes, conserved regions, transcription factor binding sites, and DNase I hypertensive sites. The regulatory features of these variants from Ensembl regulatory Build can also be mapped, which were further combined with ANNOVAR annotations. Importantly, all the functional information, especially cis-eQTL information and Ensembl regulatory features, can be included in a customized track for visualization in UCSC Genome Browser.&lt;/p&gt;&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Tue, 26 May 2015 14:13:14 -0000</pubDate><guid>https://sourceforge.net7022dce9f70bab0a3f6d7c7ca518a4e3591f160c</guid></item><item><title>Home modified by chengzhongshan</title><link>https://sourceforge.net/p/indelldplot/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;p&gt;Welcome to your wiki!&lt;/p&gt;
&lt;p&gt;This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: &lt;span&gt;[SamplePage]&lt;/span&gt;.&lt;/p&gt;
&lt;p&gt;The wiki uses &lt;a class="" href="/p/indelldplot/wiki/markdown_syntax/"&gt;Markdown&lt;/a&gt; syntax.&lt;/p&gt;
&lt;p&gt;&lt;h6&gt;Project Members:&lt;/h6&gt;
&lt;ul class="md-users-list"&gt;
&lt;li&gt;&lt;a href="/u/zhongshan0/"&gt;chengzhongshan&lt;/a&gt; (admin)&lt;/li&gt;
&lt;/ul&gt;&lt;br /&gt;
&lt;/p&gt;&lt;p&gt;&lt;span class="download-button-521f2dff3e5e8340ff90bb1c" style="margin-bottom: 1em; display: block;"&gt;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">chengzhongshan</dc:creator><pubDate>Thu, 29 Aug 2013 11:18:23 -0000</pubDate><guid>https://sourceforge.net2308086ae0cd76922d03f9eeb2316358b652a9cd</guid></item></channel></rss>