NPSDC

import yaml
from os.path import join

with open('cluster_partition.conf', 'r') as f:
    partitions = yaml.safe_load(f)

def get_partition(rule_name):
    return partitions[rule_name] if rule_name in partitions else partitions['__default__']

sim_save_dir = config['sim_save_dir']

NPSDC

getEffLen <- function(txp_len, max_len=1000, mean = 200, sd = 25)
{
  if(txp_len > max_len)
    return(txp_len-mean)
  new_mean = mean(truncnorm::rtruncnorm(n=10000, b=txp_len, mean=mean, sd=sd))
  return(ifelse(txp_len-new_mean > 0,txp_len-new_mean, new_mean-txp_len))
}

NPSDC

computeWeightedLFC <- function(y, tNodes) {
  compLFC <- function(reps, conds) {
    mC1 <- rowMeans(reps[,conds==1]) ##mean condition 1
    mC2 <- rowMeans(reps[,conds==2]) ##mean condition 2
    lfc <- log2(mC2+1) - log2(mC1+1)
    return(lfc)
  }
  
  lfcCounts <- compLFC(assays(y)[["counts"]], colData(y)[["condition"]]) ## count LFC
  varThresh <- log2(exp(1))^2*(1/rowMeans(assays(y)[["counts"]][,colData(y)[["condition"]]==1]) + 1/rowMeans(assays(y)[["counts"]][,colData(y)[["condition"]]==2])) ## threshold for variance

NPSDC

### Keybase proof

I hereby claim:

  * I am npsdc on github.
  * I am noorpratap (https://keybase.io/noorpratap) on keybase.
  * I have a public key ASDT4ICFn2-6S5XHPwliTVntQR_QQJLrOS-QRZ6MJYFwPgo

To claim this, I am signing this object:

NPSDC

### Keybase proof

I hereby claim:

  * I am npsdc on github.
  * I am noorpratap (https://keybase.io/noorpratap) on keybase.
  * I have a public key ASDT4ICFn2-6S5XHPwliTVntQR_QQJLrOS-QRZ6MJYFwPgo

To claim this, I am signing this object: