the  Collaboratory    529  Boyer  Hall    

 

Ying  Zhen  Ying  is  a  postdoc  working  jointly  with  Tom  Smith  and  

Kirk   Lohmueller   in   the   Department   of   EEB   and   Institute   of   the  

Environment   and   Sustainability   at   UCLA.   Her   current   research  

focuses  on  using  large  scale  population  genomic  data  to  learn  about  

the   demographic   history   and   natural   selection   across   a   diverse  

array  of  non-­‐‑model  taxa  from  Central  Africa.  Ying  previously  was  a  

postdoc  with  Peter  Andolfatto  at  Princeton  University,  working  on  

convergent  evolution   in  an  herbivore  community  and  evolution  of  

non-­‐‑coding  sequences  in  Drosophila  species.  She  received  her  Ph.D.  

from   Kansas   State   University   where   she   worked   with   Mark  

Ungerer  on  natural  variation  of  freezing  tolerance  in  Arabidopsis.  

Fall  2016  

 

   The   Collaboratory,   a   key  

component     of   the   Institute   for  

Quantitative   &   Computational  

Biosciences   (QCBio),   provides  

collaborative   computational  

expertise  to  all  experimental  basic  

and   clinical   life   scientists   at  

ULCA.  

 

The  Collaboratory’s  main  mission  

is   to   facilitate   genomic   data  

analysis  in  two  ways:      

 

(1)   provide   free   weekly     classes  

covering   a   number   of   topics,  

ranging   from   an   introduction   to  

UNIX   command   line   and   R   to  

specific   classes   on   RNAseq,  

ChIPseq   and   variant   calling   etc.,  

and,   (2)   provide   for   the  

opportunity   to   collaborate   with  

expert   bio-­‐‑-­‐‑   informaticians   to  

undertake   analyses   or   quality  

control  prior  analyses.  

 

Both   missions   are   accomplished  

by   a   group   of   QCBio  

Collaboratory   Fellows   funded   by  

the   QCBio   Collaboratory.   They  

represent   a   highly   selected   group  

with  proven  expert  knowledge,  as  

well   as   training   and   collaborative  

skillsets.    

The  Collaboratory  welcomes  new  Fellows:  Ying  Zhen,  Daria  Merkurijev,  Don  Vaughn,  Nick  

Mancuso,  Mike  Thompson,  Yerbol  Kurmangaliyey,  and  Motahareh  (Bahar)  Moghtadaei!  

This  issue:  New  Fellows  New  Collaboratory  Workshops  NCI  Cancer  ‘Moonshot’  B.I.G.  Summer    Recently  published  collaborations  Collaboratory  Workshop  Schedule  

 2    

Daria  Merkurjev   is  a  postdoc  at  UCLA  working   in   the   laboratories  of  Dr.   Jake  Lusis,  Dr.  

Caius  Radu,  and  Dr.  Grace  Xiao.  Dr.  Daria  Merkurjev  did  her  undergraduate  work  in  Mathematics  at  UCLA  and  

received   her   Ph.D.   in   Bioinformatics   and   Systems   Biology   at   UCSD  under   Dr.   Michael   Rosenfeld.   Her  

Ph.D.  research   focused   on   investigating   the   molecular   and   architectural   strategies   responsible   for   integrating  

genome-­‐‑wide   transcriptional   responses   to   diverse   signaling   systems   critical   for   physiological   and   behavioral  

processes   in   vertebrates.   Her   research   also   includes   understanding   the   factors   affecting   susceptibility   to  

cardiovascular  and  metabolic  disorders.  

Nick  Mancuso   is   a   post-­‐‑doctoral   fellow   in   the   Department   of   Pathology   and   Laboratory  Medicine   at   UCLA  

working  with  Bogdan  Pasaniuc.  He  is  involved  in  developing  computational  methods  to  dissect  the  genetic  basis  

for   disease.   In   addition   to  method  development,  Dr.  Mancuso   is   interested   in   applying   developed  methods   to  

large-­‐‑scale   datasets.   Prior   to   joining   UCLA   Nicholas   completed   his   PhD   in   the   bioinformatics   lab   of   Alex  

Zelikovsky  at  Georgia  State  University.    

Michael   J.   Thompson   Dr.   Michael   J.   Thompson   is   a   research   scientist   working   with   the  

laboratory  of  Prof.  Pellegrini.    Michael  received  a  BA  in  high-­‐‑energy  physics  from  Boston  University  and  a  PhD  in  

biophysics   from   the   University   of   Michigan   where   he   developed   methods   to   predict   protein   structure   from  

evolutionary  sequence  information.    His  research  in  genomics  began  as  a  postdoctoral  fellow  at  UCLA  comparing  

the  genomes  of  extremophiles  for  insight  into  the  evolution  of  protein  thermostability.    Out  of  this  work,  and  in  

collaboration  with   fellow  postdocs,   several  quantitative  genomic  analysis  methods  emerged   that  were  patented  

and  used  to  launch  a  bioinformatics  start-­‐‑up  company.    After  4  years  at  this  company,  Michael  returned  to  UCLA  

to   work   with   Prof.   David   Eisenberg   in   developing   a   method   to   predict   prion   proteins.     He   is   currently  

investigating  the  role  of  DNA  methylation  in  tumor  development  for  multiple  types  of  cancer.    

Yerbol  Kurmangaliyev  is  currently  a  postdoctoral  researcher  in  the  laboratory  of  Professor  S.  Lawrence  

Zipursky.  He  earned  a  M.S.  degree  in  Biochemistry  at  Lomonosov  Moscow  State  University  in  2006.  He  earned  a  

Ph.D.  degree  in  Bioinformatics  at  Kharkevich  Institute  for  information  transmission  problems  of  the  Russian  

Academy  of  Sciences  in  2011  under  the  supervision  of  Professor  Mikhail  S.  Gelfand.  Before  joining  UCLA  he  was  

a  postdoctoral  researcher  in  the  laboratory  of  Professor  Sergey  V.  Nuzhdin  at  USC.  His  previous  research  interests  

have  been  primarily  focused  on  the  genetic  basis  of  gene  expression.  

 

New  Collaboratory  Fellows  (continued)  

 

 3    

 

 Dr.   Motahareh   (Bahar)  

Moghtadaei.   is   joining   Dr.  

Radu’s   Lab   at   the   department   of  

Molecular   and   Medical  

Pharmacology,   UCLA   as   a  

Postdoctoral   Fellow   in  

bioinformatics.   In   collaboration  

with   Dr.   Timothy   Donahue,   Dr.  

Kym   Faull,   and   Dr.   Julian  

Whittelegge,   she  will   be  working  

on   systematic   and   integrative  

analysis   of   proteomics   and  

metabolomics   data.   Bahar  

obtained   her   PhD   in   Biomedical  

Engineering   at   Tehran  

Polytechnic   (Amirkabir  

University   of   Technology),   2009-­‐‑

2013,   and   was   a   Postdoc   at   Dr.  

Rose’s   Lab   at   the   Department   of  

Physiology   and   Biophysics,  

Faculty   of   Medicine,   Dalhousie  

University,   Canada,   2014-­‐‑2016.  

Her   general   research   interests  

include   algorithm   development,  

and   computer   programming   for  

biomedical  research.  

 

 

 

NEW  Collaboratory  Workshops    Cancer  Genomics  -­‐‑  with  Catie  Grasso  Cancer  Genomics  will  cover  the  fundamentals  of  analyzing  tumor  

genomics   data,   including   exome   and   transcriptome   sequencing,  

and   using   it   in   a   translational   setting   to   identify   diagnostic  

biomarkers  and  drivers   that   can  be  drug   targeted.    We  will   cover  

the   fundamentals   of   calling   somatic   aberrations,   including   point  

mutations,   indels,   rearrangements   and   copy   number   alterations  

with   an   eye   to   immediate   application.     We   will   discuss   targeted  

sequencing   versus   exome   sequencing   versus   whole   genome  

sequencing  and  how  they  differ   in   terms  of  methodology,   time  to  

results  and  cost   in   the  context  of  diagnostic   testing.      We  will  also  

discuss  the  integration  of  drug  screen  data,  other  high-­‐‑throughput  

functional   data   data,   including   germline   genetics   and  

epidemiology,  and  experimental  results,  and  also  pathway  data  for  

understanding   underlying   cancer   biology   and   finally   we   will  

discuss  how  to  use  this  information  to  decide  the  best  therapeutic  

strategy.  

 

Intro  to  Modern  Statistics  -­‐‑  with  Don  Vaughn  Traditional   statistical   analysis   emerged   in   the   pre-­‐‑computer   age,  

and  correspondingly,  nearly  all  tractable  methods  required  closed-­‐‑

form  (you  can  write  them  in  a  single  equation)  solutions.    

Attached  to  these  methods  (t-­‐‑test,  chi-­‐‑squared,  Pearson  correlation,  

regression,  etc),  however,  are  a  number  of  assumptions  about   the  

data:   Gaussian   distribution,   homoscedasticity,   linearity,   equal  

variances,  continuity,  large  sample  size  to  name  a  few.    

In  nearly  every  dataset  with  which  research  scientists  work,   these  

assumptions   are   rarely   all   met.   Journals   and   reviewers   are  

increasingly   scrutinizing   and   rejecting   submissions   that   apply  

traditional  statistics  when  their  requirements  are  not  met.    

Fortunately,   resampling   techniques   like   bootstrapping   and  

permutation   tests   make   far   fewer   assumptions   about   the  

underlying   data   and   can   thus   be   applied   much   more   generally  

than  traditional  statistics.  

 

 4    

Schedule  of  Collaboratory  Workshops    Please  follow  links  for  full  workshop  descriptions.  Classes  are  held  in  Boyer  Hall  529.    9/27-­‐‑9/29,  Workshop  4:  Galaxy  for  NGS  Data  Analysis,  1:00pm      10/4-­‐‑10/6,  Workshop  13:  Cancer  Genomics,  9:30am-­‐‑12:00pm    10/4-­‐‑10/6,  Workshop  5:  RNA-­‐‑seq  Analysis,  1:00pm    10/11-­‐‑10/13,  Workshop  3:  Intro  to  R,  9:30am    10/18-­‐‑10/20,  Workshop  8:  Variant  Calling,  10:30am    10/25-­‐‑10/27,  Workshop  9:  Python,  10:00am    11/1-­‐‑11/3,  Workshop  10:  Hi-­‐‑C,  1:00pm    11/8-­‐‑11/10,  Workshop  11:  Metagenomics  Analysis,  9:30am    11/8-­‐‑11/10,  Workshop  13:  Cancer  Genomics,  1:00pm-­‐‑3:30pm    11/15-­‐‑11/17,  Workshop  1:  Intro  to  UNIX,  2:00pm    11/29-­‐‑12/1,  Workshop  2:  Using  NGS  Analysis  Tools,  1:00pm    12/6-­‐‑12/8,  Workshop  6:  BS-­‐‑Seq,1:00pm    12/6-­‐‑12/8,  Workshop  13:  Cancer  Genomics,  9:30am-­‐‑12:00pm      

 

 

 

 

 

 

 

 

 5    

B.I.G.  Summer  2016  

By  Ina  Thorner  

QCBio’s   eight   week   undergraduate   summer   research   program,   Bruins-­‐In-­‐Genomics   (B.I.G.)  Summer,  came  to  an  end  on  August  12th  after  an  exciting  summer.    

Thirty-­‐seven  students  attended  Collaboratory  workshops  and  contributed  to  research  in  the  labs  of  QCBio  faculty.    

 

“My   BIG   summer   student   was   outstanding!   She   contributed   greatly   to   the  analysis  of  an  RNA-­‐seq  dataset,  while  working  almost  entirely  independently.  She  went   above   and   beyond   my   expectations   in   terms   of   analysis,   background  reading,   and   preparation   for   her   lab   meeting   and   poster.   She   will   make   a  fantastic  graduate  student  if  she  chooses  that  route,”  said  postdoctoral  fellow  Jeff  Rasmussen  from  the  Sagasti  Lab.  

B.I.G.   Summer   students   also   participated   in   professional   development   workshops,   journal   club,  weekly  seminars,  and  a  concluding  poster  session.    

B.I.G.   Summer   student   Scott   De   Taboada   said,   “Honestly   I   felt   that   this   program   was   amazing.  Coming  in  I  wasn't  sure  if  graduate  school  was  a  path  I  wanted  to  take.  This  program  showed  me  the  opportunities   I  would  have  and  gave  me  a  great  understanding  of  what   it  would  take  to  get  a  PhD.”  

B.I.G.   Summer   student   Brenda   Ji   said,   “B.I.G.   Summer   has   influenced   my   thoughts   on   graduate  school  pretty  drastically.  Before  this   I  was  pretty  set  on  medical  school  and  didn't   think  graduate  school  would  be  the  right  fit  for  me,  but  now  that  I  have  seen  the  demand  for  bioinformatics  and  the  need   for  people  with   computer   science  backgrounds,   it  has   really   changed   the  way   that   I   see  my  future.  Now,  I'm  not  so  sure  if  I  want  to  go  to  medical  school,  but  graduate  school  sounds  fun  and  exciting  and  rewarding.  My  home   institution   is  a   small   liberal  arts   college  where   I  had  very   little  exposure  to  bioinformatics,  but  I  love  both  biology  and  computer  science,  so  this  has  been  a  really  valuable  and  enriching  experience  for  me.”  

The  program  culminated  with  a  poster  session  and  awards  ceremony.  

 6    

UCLA  Collaboratory  

Takes  First  Step  in  

NCI  Cancer  

'ʹMoonshot'ʹ    

By  Catie  Grasso  

In   the   last   few   years,   multiple  

new  drug  treatment  strategies  for  

untreatable   metastatic   cancers  

have   ignited   new   hope   for  

progress   in   cancer  

treatment.     Immunotherapy  

techniques,   including   PD-­‐‑1  

inhibitors,  have  been  putting  90%  

of   patients   who   had   failed  

standard   of   care   into   one   to   two  

year   remissions   for   multiple  

cancer   types.     Similarly,   drugs  

targeting   patients   with   DNA  

repair   deficiencies,   like   PARP  

inhibitors,   have   been   yielding  

similar   responses   in   other  

terminal   patients   (88%   response  

rate).     These   are   unparalleled  

response   rates.     The   advent   of  

next   generation   sequencing  

techniques   able   to   rapidly   and  

affordably  monitor   response  and  

resistance  during  treatment  make  

possible   the   development   of  

combined   approaches   and   new  

options   in   real   time   with   living  

patients.      

The   NIH   National   Cancer  

Institute   Cancer   Moonshot  

initiative   is   about   making   these  

treatment   options   as   effective   as  

possible,   as   quickly   as   possible,  

and   the   new   UCLA   Parker  

Institute   for   Cancer  

Immunotherapy   led  by  Dr.  Toni  

Ribas,   an   innovator   in   cancer  

immunotherapy   and   targeted  

gene   therapy,   is   a   key   part   of  

that   push.     This   fall   I   will   be  

teaching   a   one   week   course   on  

the  basics  of  cancer  genomics,  as  

well  as   introducing  cutting  edge  

approaches.     The   course   is   open  

to   anyone   interested,   and   a   key  

goal   is  mobilizing   each   person’s  

existing   skills   now   to  help   them  

contribute   to   this   exciting   new  

initiative  with   an   eye   to   rapidly  

impacting  patient  care.  

 

Dr.  Catherine  Grasso  is  an  

Adjunct  Assistant  Professor  in  

Hematology  Oncology  and  

Director  of  Bioinformatics  for  the  

UCLA  Parker  Institute  of  Cancer  

Immunotherapy.      

Recently  Published  

Collaborations  

CRISPR/Cas9-­‐‑mediated  correction  of  the  sickle  mutation  in  human  CD34+  cells.  Mol  Ther.  2016  Jul  13.  doi:    10.1038/mt.2016.148.  [Epub  ahead  of  print]  

Hoban  MD,  Lumaquin  D,  Kuo  CY,  Romero  Z,  Long  J,  Ho  M,  Young  CS,  Mojadidi  M,  Fitz-­‐‑Gibbon  S,  Cooper  AR,  Lill  GR,  Urbinati  F,  Campo-­‐‑Fernandez  B,  Bjurstrom  CF,  Pellegrini  M,  Hollis  RP,  Kohn  DB. Antibody-­‐‑Mediated  Rejection  in  Lung  Transplantation:  Clinical  Outcomes  and  Donor-­‐‑Specific  Antibody  Characteristics.  Am  J  Transplant.  2016  Apr;16(4):1216-­‐‑28.  doi:  10.1111/ajt.13589.  Epub  2016  Feb  4.  PubMed  PMID:  26845386.    1:  Roux  A,  Bendib  Le  Lan  I,  Holifanjaniaina  S,  Thomas  KA,  Hamid  AM,  Picard  C,  Grenet  D,  De  Miranda  S,  Douvry  B,  Beaumont-­‐‑Azuar  L,  Sage  E,  Devaquet  J,  Cuquemelle  E,  Le  Guen  M,  Spreafico  R,  Suberbielle-­‐‑Boissel  C,  Stern  M,  Parquin  F;  Foch  Lung  Transplantation  Group.      Genomic  Flatlining  in  the  Endangered  Island  Fox.  Curr  Biol.  2016  Apr  20.  pii:  S0960-­‐‑9822(16)30173-­‐‑7.  doi:  10.1016/j.cub.2016.02.062.  [Epub  ahead  of  print]  PubMed  PMID:  27112291.    

 

 

 Collaboratory  Services   Analyses  Service  

The  Collaboratory  has  

implemented  computational  

methods  and  procedures  to  

analyze  sequencing  data  for  the  

UCLA  community.  

We  have  developed  pipelines  that  

are  specifically  designed  to  

optimize  the  use  of  the  hoffman2  

cluster  resources.  

As  part  of  this  service,  QCB  

Collaboratory  fellows  will  

analyze  next  generation  

sequencing  data  submitted  to  us,  

and  provide  users  with  their  

results.  Examples  of  data  that  we  

can  analyze  include  RNA-­‐‑seq,  

ChIP-­‐‑seq,  and  bisulfite  seq,  and  

we  can  also  perform  variant  

calling  on  whole  genomes  or  

exomes.  

Please  contact  Matteo  Pellegrini  

matteop@mcdb.ucla.edu,  if  you  

are  interested  in  participating.  

The  service  is  provided  at  no  cost  

to  users,  but  we  do  ask  that  the  

collaboratory  fellow  that  analyzes  

your  data  be  acknowledged  as  an  

author  on  any  eventual  

publications.  

Genome  Browser  Tools  

The  Collaboratory  hosts  and  administers  a  local  server  for  the  UCSC  genome  browser  tools  that  allows  users  to  view  genomic  data  associated  with  genomes  not  supported  by  the  UCSC  site.  

It  contains  the  following  major  features:  

●Graphical  display  of  genes,  gene  structures,  and  gene  annotations  

●blat  alignment  of  DNA  sequences  with  a  reference  custom  genome  

●Graphical  display  of  custom  tracks  with  existing  genomic  annotation  tracks  

The  common  uses  of  the  genome  browser  for  NGS  data  analysis  include:  

●display  and  view  gene  expression  profiles  

●examine  genomic  data  base-­‐‑by-­‐‑base  

●display  and  examine  genomic  variations  

●parallel  compare  genomic  data  derived  from  different  technologies,  such  as  NGS  and  microarray  

●share  genomic  date  with  collaborators  

●Prepare  figures  for  publications