HarappaWorld HRP0289-HRP0297

Posted by on May 21, 2013 17 comments

I have added the HarappaWorld Admixture results for HRP0289-HRP0297 to the individual spreadsheet.

Do note that the admixture components do not necessarily represent real ancestral populations. Also, the names I have chosen for the components should be thought of as mnemonics to ease discussion. I chose them based on which populations in my data these components peaked in. They do not tell anything directly about ancestral populations. The best way to look at these admixture results is by comparing individuals and populations. Finally, the standard error estimates on these results can be about 1%. Therefore, it is entirely possible that your 1% exotic admixture result is just noise.

I also updated the results for HRP0274 using FTDNA Family Finder data instead of the Genographic 2.0 data that was originally submitted. As the Geno2 data has only 14,000 SNPs in common with my HarappaWorld calculator, it's interesting to see HRP0274's admxiture results change:

Component Geno2 FTDNA
South Indian 48.68% 46.00%
Baloch 34.22% 32.99%
Caucasian 4.33% 5.02%
Northeast Euro 3.89% 3.57%
Southeast Asian 2.75% 1.06%
Siberian 1.25% 1.87%
Northeast Asian 1.16% 1.69%
Papuan 1.14% 1.85%
American 0.87% 1.23%
Beringian 0.01% 1.23%
Mediterranean 0.00% 0.39%
Southwest Asian 1.69% 3.10%
San 0.00% 0.00%
East African 0.00% 0.00%
Pygmy 0.00% 0.00%
West African 0.00% 0.00%

The only differences greater than 1% are South Indian (2.68%), Southeast Asian (1.69%), Southwest Asian (1.41%), Baloch (1.23%), and Beringian (1.22%). It's remarkable that only 14,000 SNPs could provide us a decent result.

We have two new Gujarati participants. HRP0292, a Gujarati Jain, seems to be more similar to somewhat southern populations. HRP0294, a Gujarati Sunni Vohra, has results somewhat similar to HRP0265 (Gujarati Patel Muslim) and more north-oriented. Therefore, I have separated a new ethnic category of Gujarati Muslims in my ethnic spreadsheet. I'll have averages when I compute them next time.

We have two Indian adoptee participants as well. HRP0297 has results which match well with the Bengalis (other than the Brahmins) in this project. HRP0290's results are somewhat harder to figure out. The closest groups, not too close, are probably Tharu from Uttarakhand and Satnami from Chhattisgarh (Reich et al dataset). A ChromoPainter analysis would be more useful here.

HarappaWorld HRP0284-HRP0288

Posted by on April 22, 2013 98 comments

I have added the HarappaWorld Admixture results for HRP0284-HRP0288 to the individual spreadsheet.

Do note that the admixture components do not necessarily represent real ancestral populations. Also, the names I have chosen for the components should be thought of as mnemonics to ease discussion. I chose them based on which populations in my data these components peaked in. They do not tell anything directly about ancestral populations. The best way to look at these admixture results is by comparing individuals and populations. Finally, the standard error estimates on these results can be about 1%. Therefore, it is entirely possible that your 1% exotic admixture result is just noise.

I have also updated the group averages (weighted) spreadsheet.

HarappaWorld HRP0273-HRP0283

Posted by on March 27, 2013 46 comments

I have added the HarappaWorld Admixture results for HRP0273-HRP0283 to the individual spreadsheet.

I got two participants from the Geno 2.0 Project. While I have calculated their HarappaWorld Admixture results, please note that Geno2 has only about 14,000 SNPs in common with HarappaWorld. Thus these results are very noisy.

Do note that the admixture components do not necessarily represent real ancestral populations. Also, the names I have chosen for the components should be thought of as mnemonics to ease discussion. I chose them based on which populations in my data these components peaked in. They do not tell anything directly about ancestral populations. The best way to look at these admixture results is by comparing individuals and populations. Finally, the standard error estimates on these results can be about 1%. Therefore, it is entirely possible that your 1% exotic admixture result is just noise.

We got our first Pashtun participants, one Afghan and one Pakistani. Both have very similar results and are not much different than the HGDP Pathan sample average in their South Indian component.

HRP0278, a Bengali (mostly), is more East Asian components than any other Bengali participants (including my friend Razib.)

HarappaWorld HRP0253-HRP0272

Posted by on January 29, 2013 8 comments

I have added the HarappaWorld Admixture results for HRP0253-HRP0272 to the individual spreadsheet.

I got two participants from the Geno 2.0 Project. While I have calculated their HarappaWorld Admixture results, please note that Geno2 has only about 14,000 SNPs in common with HarappaWorld. Thus these results are very noisy.

Do note that the admixture components do not necessarily represent real ancestral populations. Also, the names I have chosen for the components should be thought of as mnemonics to ease discussion. I chose them based on which populations in my data these components peaked in. They do not tell anything directly about ancestral populations. The best way to look at these admixture results is by comparing individuals and populations. Finally, the standard error estimates on these results can be about 1%. Therefore, it is entirely possible that your 1% exotic admixture result is just noise.

23andme Now $99

Posted by on December 14, 2012 9 comments

Things have been very busy in meatspace in recent months, but I am finally back.

While the submission of data from new participants has really slowed, the release of new software continues unabated. I hope to try some of them (ALDER, MULTIMIX, ADMIXTOOLS, etc.) out and report anything interesting here.

Another disappointment has been the 1000genomes South Asian data which is still nowhere to be seen.

However, 23andme has reduced its regular price to $99 which should induce some of you to test and participate.

The Genographic Project has finally gotten into autosomal testing. If you are South Asian and have received their Geno 2.0 results, I would be interested in your raw data so that I can check how many SNPs it has in common with HarappaWorld.

Eurasian ChromoPainter Chunk Counts

Posted by on August 30, 2012 5 comments

Continuing with the Eurasian ChromoPainter analysis, here is the zip file containing the chunk counts that were donated by an individual in a column to an individual in a row. Please note that this is an all-against-all analysis, so it does not directly show the direction of gene flow. Also, the IDs I used here are based on ethnicity (except for harappann which are mixed Harappa Project participants). If you want to find out your ethnicID, take a look at this spreadsheet which has the appropriate mapping.

Since fineStructure classified these 2,001 individuals into 203 populations, it's easier to look at the chunk counts averaged over these populations.

From top to bottom (recipient) and left to right (donor), the five major branches are South Asian, European, Near Eastern & Western Asian, Inner Asian/Siberian, and East Asian respectively.

This population chunk count data is available in a spreadsheet.

Now, let's look at some specific recipient clusters/populations.

Here's the top 50 populations that have donated chunks to the Kalash (Pop133).

The three bars at the bottom are for the 3 different (closely related) Kalash clusters. The clusters donating the most after that are the Burusho, Sindhi, Pathan, etc. The top non-South Asian donor (Tajik Pop116) is at #21 and the next one is also Tajik (Pop95) at #38.

Now here are the top donors for the Pathans (Pop148).

Interestingly, the number of chunks donated to Pathans from Balochi, Brahui and Sindhi seems to be a bit more than from Punjabis. Again, Tajiks are the closest non South Asian group at #55 and #59, followed by Kurds at #62 and Iranians/Kurds cluster (Pop172) at #63.

Now let's look at the donors for Pop134 which includes 2 Bhatia, 2 Gujarati-B, 3 Haryana Jatt, 1 Kashmiri, 4 Pathan, 5 Punjabi, 1 Punjabi Brahmin, 5 Punjabi Jatt, 2 Punjabi Ramgarhia, 1 Rajasthani Brahmin, 1 Sindhi and 3 Singapore Indians.

The top donors (other than Punjabis, of course) are Sindhis and Gujarati-B. The top non South Asian donors are Tajiks at #65 & #67, Iranians/Kurds at #69, Turkmen at #70, Kurds at #73 and Lezgin at #75.

Now for Pop181 (2 Baloch and 9 Brahui).

The Baloch/Brahui are more inbred compared to Punjabis and Pathans. After teh top donors from Baloch, Brahui and Makrani, we get Sindhis, Pathans, Velama and Punjabis. The top non South Asian donor populations are Iranian/Kurd at #28, Turkmen at #33, Turk/Kurd (Pop162) at #35, Iranian Jews at #39, Kurd at #41, a lone Saudi at #42, Iraqi Jews at #43, Tajik at #44, Drue at #47, Armenians at #48, and Samaritian at #50. So it seems like Baloch and Brahui are a lot more West Asian than other groups in Pakistan/NW India.

Let's look at the donors for Pop129 (1 Tamil Nadu Brahmin, 4 Iyengar Brahmin, 8 Iyer Brahmin, and 9 Singapore Indians).

The top donors, after Pop129, are Iyengar Brahmins and a group consisting of other South Indian Brahmins, Kerala Christiand and Nairs, and then Velama. The Dusadh are the top north Indian donor, followed by Gujarati-B and Chamar. Top non South Asian donor is Tajik at #73.

Now for the top donors for Pop188 which includes 33 Singapore Indians, 4 Tamil Vellalar, 3 Andhra Pradesh Reddy, 2 Andhra Pradesh, 2 Dusadh, 2 Karnataka, 2 Sinhalese, 2 Tamil Nadar, 2 Tamil Nadu Scheduled Caste, 1 Chenchu, 1 Kerala Christian, 1 Kerala Muslim, 1 North Kannadi, 1 Tamil Muslim, 1 Tamil Vishwakarma and 1 Velama.

The top donors are Sakilli, Piramalaikallar, and Velama. Their top non South Asian donor is a group of 5 Singapore Malays at #72, followed by Romanian and Serbian Romany at #73.

Finally, let's see which clusters are the top donors for Paniya (Pop65) who get the most South Indian component in my HarappaWorld Admixture runs.

Their top donors are Paniya, Malayan, Pulliyar and Kurumba. Their top non South Asian donors are Singapore Malays at #55, Burmanese at #59, and Cambodian/Singapore Malay at #64.

Eurasian fineStructure Dendrograms

Posted by on August 16, 2012 22 comments

The dendrogram in the last post about Eurasian ChromoPainter/fineStructure analysis is a little hard to make sense of, so here is the same info in a better format.

First, the upper portion showing the relationship of the five branches:

Now, let's take a look at Branch1 which consists of South Asians:

Branch2 is European.

Branch3 is mostly the Near East and western Asia.

Branch4 is Inner Asia/Siberia.

And Branch5 is East Asian.

Note that the leaf labels consist of ethnicity followed by the number of that group who belong to that particular cluster. However, some of the labels are cut off in the images since they were long.

Eurasian ChromoPainter Analysis

Posted by on August 15, 2012 2 comments

Some months ago, I decided to run a big ChromoPainter analysis of the Eurasian samples I have. I removed from my dataset not only all Sub-Saharan Africans, but also North Africans and anyone else with more than 2% African admixture (which unfortunately included me).

Since the number of samples was still too large, I picked 25 random individuals from each non-South-Asian ethnicity while keeping all South Asians. I also tried to remove all close relatives and those with a high missing genotyping rate.

In the end, I had 254,576 SNPs for 2,001 samples belonging to 197 ethnic groups.

I ran ShapeIT to phase their genomes and then ChromoPainter and fineStructure. The whole process took about 2 months.

Then I got busy and the results sat on my computer for more than a month.

Now let's look at the ChromoPainter/fineStructure analysis. Due to my time constraints, I am going to present them in several posts.

Today, let's look at the fineStructure clustering run on the chunkcount output of ChromoPainter. It divided the individuals into 203 populations. Here's the spreadsheet containing the group and individual population clustering.

And here is the dendrogram showing the relationship of the clusters/populations computed by fineStructure.

UPDATE: Better dendrograms

23andme $50 Off

Posted by on August 9, 2012 1 comment

23andme has a $50 off coupon sale for three days. Here's the email I got from them:

Visiting family this summer? Are they part of 23andMe? Take advantage of our summer discount: $50 OFF each kit you purchase. This offer expires in 3 days (11:59PM PDT, Sunday August 12, 2012).

To use this code, visit our online store and add an order to your cart. Click "I have a discount code" and enter the code below.

$50 off Discount code: VMQ6KG

HarappaWorld HRP0250-HRP0252

Posted by on August 6, 2012 5 comments

I have added the HarappaWorld Admixture results for HRP0250-HRP0252 to the individual spreadsheet.

However, I have not recomputed the weighted averages for the Kashmiris or Bengali Brahmins. Also, I am not sure about Tamil Gounder. Wikipedia says they are Vellalars, but I don't know if I should report separate Gounder results or include in the Tamil Vellalar average.

Do note that the admixture components do not necessarily represent real ancestral populations. Also, the names I have chosen for the components should be thought of as mnemonics to ease discussion. I chose them based on which populations in my data these components peaked in. They do not tell anything directly about ancestral populations. The best way to look at these admixture results is by comparing individuals and populations. Finally, the standard error estimates on these results can be about 1%. Therefore, it is entirely possible that your 1% exotic admixture result is just noise.